Category Archives: Data Science
Companies hiring data scientists in NYC and how much they pay – Business Insider
Data science is a fast-growing field. According to the Bureau of Labor Statistics, it's growing much faster than the average occupation and is expected to continue to grow through 2029. In 2018, LinkedIn found that there was a shortage of over 150,000 people in the data science field.
Insider examined data from the US Office of Foreign Labor Certification, LinkedIn, and company job sites to understand salaries in the data science world, and who is currently hiring.
When a US company wants to hire someone from another country, the company has to file for a visa through the US Office of Foreign Labor Certification. The visa applications, which are published online, include salary data that is helpful in understanding how specific firms compensate employees.
The most common visa is called an H-1(B) visa, which is used for most professional positions. It's worth noting that the information only represents salary, and excludes other types of compensation like bonuses and benefits that most employees receive.We looked at visa applications from 2018 to 2020 for each firm.
Let's dig into what Google, Facebook, Spotify, Aetna, and more pay data scientists in New York City, and the positions that are open as of January 4.
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Companies hiring data scientists in NYC and how much they pay - Business Insider
Which Technology Jobs Will Require AI and Machine Learning Skills? – Dice Insights
Artificial intelligence (A.I.) and machine learning seem poised to dominate the future. Companies everywhere are pouring resources into making their apps and services smarter. But which technology jobs will actually require A.I. skills?
For an answer to that question, we turn to Burning Glass, which collects and analyzes millions of job postings from across the country. Specifically, we wanted to see which professions had the highest percentage of job postings requesting A.I. skills. Heres that breakdown; as the clich goes, some of these results may surprise you:
What can we conclude from this breakdown? Although you might think that artificial intelligence skills are very much in demand among software developers and engineers (after all, someone needs to build a smarter chatbot), data science is clearly the profession where A.I. is most in vogue.
Indeed,theres a lot of overlap between A.I. and data science. Both disciplines involve collecting, wrangling, cleaning, and analyzing massive amounts of data. But whereas a data scientist will analyze data for insights that they present to the broader organization, artificial intelligence and machine learning experts will use those datasets to train A.I. platforms to become smarter. Once sufficiently trained, those platforms can then make their own (hopefully correct) inferences about data.
Given that intersection of artificial intelligence and data science, many machine-learning and A.I. experts become data scientists, and vice versa. That relationship will likely only deepen in the years ahead. Burning Glass suggests that machine learning is a defining skill among data scientists, necessary for day-to-day tasks; if youre aiming for a job as a data scientist, having extensive knowledge of artificial intelligence and machine-learning tools and platforms can give you a crucial advantage in a crowded market.
Many other technologist roles will see the need for artificial intelligence skills increase in the years ahead. If youre involved in software development, for instance, learning A.I. skills now will prepare you for a future in which A.I. tools and platforms are a prevalent element in many companies tech stacks. And make no mistake about it: Managers and executives will alsoneed to become familiar with A.I. concepts and skills.A.I. is not going to replace managers but managers that use A.I. will replace those that do not, Rob Thomas, senior vice president of IBMscloudand data platform,recently told CNBC.
Overall, jobs utilizing artificial intelligence skills are projected to grow 43.4 percent over the next decade; the current median salary for jobs that heavily utilize A.I. skills is $105,000, higher than for many other professions. It must be noted, though, that A.I. and machine learning are areas where you really need to know your stuff, and hiring managers will surely test you on both your knowledge of fundamental concepts as well as your ability to execute. When applying for A.I.-related jobs, a portfolio of previous projects can only help your prospects.
Granted, its still early days for A.I.: Despite all the hype, relatively few companies have integrated A.I. into either their front-end products or back-end infrastructure. Nonetheless, its clear that employers are already interested in technologists who are familiar with the A.I. and machine learning platforms that will help determine the future.
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Which Technology Jobs Will Require AI and Machine Learning Skills? - Dice Insights
This Is the Best Place to Buy Groceries, New Data Finds | Eat This Not That – Eat This, Not That
If you asked someone what their favorite place to get groceries is, would you be surprised if they said Amazon? A new report reveals that it's the top place to shop for groceries, based on consumers' preferences.
According to dunnhumby, the global leader in consumer data science, Amazon reigned supreme in the platform's fourth annual Retailer Preference Index (RPI)an exhaustive, nationwide study of best places to buy groceries, which takes consumers' emotional connection to grocery chains as well as prices into consideration. (Related: 8 Grocery Items That May Soon Be in Short Supply.)
In the report, dunnhumby surveyed roughly 10,000 U.S. households about their preferred grocers, and of the 56 retailers included, Amazon dominated the scene. It received the highest overall customer preference score in the first quartile. Behind Amazon is the former winner, H-E-B, followed by Trader Joe's, Wegman's, and Aldi's.
Last year, Amazon placed third in the overall RPI but has now jumped to first place, primarily because of how well-positioned it was to deliver on many of the key areas measured in the index such as speed (second place) and digital (first place). The online retailer took 11th place in the price category, ensuring a strong product value.
The report evaluated seven drivers of customer preference, including price, quality, digital, operations, convenience, discounts, rewards & information, and speed. In addition, it assessed how likely a retailer's customer value proposition will set the company up for long-term financial success.
As of this year, the data science platform also factored in a Covid Momentum Metric, which explores the short-term financial successes each retailer experienced during the pandemic, and Amazon (to no surprise) claimed the first spot in that category, as well.
"Amazon accelerated past every other retailer on our Covid Momentum Metric and customer safety ratings, due to its speed to shop and virtual store format. As we begin to emerge from the pandemic, we should expect value perception to come back strongly. Beyond Covid, retailers with Customer First strategies will best adapt to changing behaviors and deliver what matters most to their customers," said Grant Steadman, President of North America for dunnhumby in a statement.
For more, be sure to check out6 Grocery Stores That Are Already Offering the COVID-19 Vaccine.
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This Is the Best Place to Buy Groceries, New Data Finds | Eat This Not That - Eat This, Not That
Associate Professor of Fisheries Oceanography named a Cooperative Institute for the North Atlantic Region (CINAR) Fellow – UMass Dartmouth
Gavin Fay was honored by CINAR for his work on sustainable fisheries management
The Cooperative Institute for the North Atlantic Region (CINAR) recently announced five new Quantitative Fisheries and Ecosystems Science Fellows, including Associate Professor Gavin Fay (Fisheries Oceanography). CINAR, which is led by the Woods Hole Oceanographic Institution and the Northeast Fisheries Science Center, is a consortium of research institutions focused on the marine ecosystem in the North Atlantic. CINAR also works closely with the federal National Oceanic and Atmospheric Administration.
Fay was chosen for this important fellowship due to his research that utilizes statistical and mathematical models for better ecosystem-based decision making for fisheries and oceans. As a Fellow, he is interested in both developing new methods for statistical modeling, fisheries assessment, and ecosystem-based management; and, how open data science tools can empower communication of scientific results for application to management and policy.
Im thankful to receive this award and support from CINAR, NEFSC, and the NOAA QUEST program. The fellowship will help us expand and strengthen the School for Marine Science and Technologys collaborations with NOAA NEFSC to provide the science (and future workforce) that will support decisions to manage our oceans and fisheries and help sustain thriving coastal communities in the face of regional and global change, said Fay.
According to CINAR, The goal of the fellowship program is to engage early-career scientists in research that supports the training and education of the next generation of stock assessment scientists, ecosystem scientists, and economists, and that improves the assessment and management of living marine resources in the Northeast U.S.
The CINAR fellowship will allow Fay to provide training workshops in quantitative fisheries science at the School for Marine Science and Technology (SMAST) for students from CINAR partner institutions. This opportunity will help connect UMassD students with their regional peer network and agency staff. As a fellow, Fay will also lead a national skills-based conference in quantitative fisheries science, to be targeted towards students at institutions that do not have academic training programs in these methods, to increase the national capability for applying the interdisciplinary advice needed to sustain oceans and fisheries.
Im excited that these activities will engage our students with hands-on learning of state-of-the-art statistical methods and decision support tools and have them interact and learn with their peers at the other CINAR institutions in the Northeast, stated Fay. Im humbled to join this cohort of fellows; Drs Cullen, Nesslage, Stoll, and Wiedenmann are all excellent fisheries scientists and educators. Looking forward to working with them all.
Members of CINAR include the UMass Dartmouth School for Marine Science and Technology (SMAST), the Woods Hole Oceanographic Institution, the Gulf of Maine Research Institute, Rutgers University, University of Maryland Center for Environmental Science, University of Maryland Eastern Shore, University of Maine, and the University of Rhode Island.
At SMAST, Fay teaches courses in statistics, ecological population modeling, science communication, and Ecosystem-Based Fisheries Management. He currently serves on the Mid-Atlantic Fishery Management Council's Scientific and Statistical Committee, as well as the New England Fishery Management Council's Ecosystem-Based Fisheries Management Plan Development Team. He is a scientific advisory NETwork member for Eating with the Ecosystem, a local nonprofit organization working to promote a place-based approach to sustaining New England's wild seafood.
SMAST Fisheries Oceanography, News and Public Information, School for Marine Science and Technology
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Rapid Insight To Host Free Webinar, Building on Data: From Raw Piles to Data Science – PR Web
Free Webinar: January 12th, 2 PM ET | 11 AM PT
CONWAY, N.H. (PRWEB) January 11, 2021
Organizations frequently hire data practitioners to build a new data infrastructure from the ground up, but many lack a formal data strategy or implementation plan. On Tuesday, January 12th at 2 PM ET (11 AM PT), analytics software provider Rapid Insight will host a free webinar offering foundational advice for structuring an organizations data.
The webinar will feature Caitlin Hudon, Lead Data Scientist at OnlineMedEd. Hudon will walk through establishing a new data infrastructure at an organization, assembling the tools and processes required to succeed, and building a culture of data for continued success. The webinar will also feature Jon MacMillan, Product Manager at Rapid Insight.
In addition to an overview of establishing an effective greenfield data program, Hudon will offer advice on creating immediate value with data while laying a foundation for long-term success. She will discuss establishing a communications plan and intake system for data requests and developing a data dictionary for team members and end-users.
For analysts tasked with setting their organization up for success with data, this webinar will be a valuable resource, said Mike Laracy, President and Founder of Rapid Insight. Hudons experience and wisdom will help you assemble an actionable plan, and Rapid Insights intuitive tools and expert analyst support can help you execute it.
This webinar explores a highly-relevant topic. Organizations around the world are recognizing the value of structured data and hiring analysts to operationalize it. This webinar will equip those assigned to organize and analyze unstructured data with a clear path toward building data science.
To learn more about this webinar and to register, click here.
About Rapid Insight:Rapid Insight is a leading provider of business analysis and automated predictive analytics software. With a specialty in higher education and a focus on ease of use and efficiency, Rapid Insight products enable users to turn their raw data into actionable information. The companys analytic software simplifies the extraction and cleansing of data, equipping organizations of all sizes with data-informed decision making. For more information, visit http://www.rapidinsight.com.
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Rapid Insight To Host Free Webinar, Building on Data: From Raw Piles to Data Science - PR Web
Data Science for Social Good Programme helps Ofsted and World Bank – India Education Diary
Data Science for Social Good (DSSGxUK)is a summer programme that has been hosted by theUniversity of WarwickandThe Alan Turing Institutefor the last two years, and will this summer, 2021, be delivered by University of Warwick in collaboration with Ludwig Maximillian University (Munich) under the DSSGx UK chapter of theDSSG Foundation.
DSSG is the brainchild of Rayid Ghani, former Chief Scientist for President Obama, and continues to be run in the US at Carnegie Mellon University. Participants are trained over the summer, and work on data science projects with not-for-profit organisations and governmental bodies, helping them leverage their data to improve their services, interventions and outreach.
This summer, over 2020, a congregation of data scientists from all over the world collaborated virtually, and successfully designed a new prioritisation system forOfsted the Office for Standards in Education, to help them inspect and regulate early years care providers, as well as a new public administration corruption risk identification and analysing system forWorld Bank, an international financial institution who provide loans and grants to the governments of developing countries for the purpose of pursuing capital gains.
Nitya Raviprakash was a participant in the programme this summer for the World Bank project, and comments:
DSSGx-UK was a great programme where I picked up many cool technical skills, but the best part about it was the people some of the most genuine and kind people Ive ever worked with (and learned so much from), who really want to make a positive impact on the world. To me, thats what made the experience so beautiful.
Alexandra Habershon from World Bank comments:
We were really impressed with what the team achieved in just a few weeks. They embraced the anticorruption data challenge with enormous enthusiasm, creativity and skill. We came away with new analytic methods, structured data sets, instructions for researchers to take the work further, and insights about gaps in public sector data.All of this will help inform the advice we provide to governments on strengthening their accountability systems. It will also contribute to the World Banks ongoing anticorruption research program with academic and development partners.
James Bowsher-Murray, Head of Early Years and Social Care Data and Insight, from Ofsted, comments:
I was impressed with the modelling and insight that the team were able to produce in such limited time. We are now looking forward to running and testing the model in Ofsted and seeing how it can help improve the quality of early years care that children receive.
After such a successful year the University of Warwick are proud to announce that the programme is returning for summer 2021, in collaboration with the Ludwigs Maximillian University in Germany, with support from The Alan Turing Institute.
The 12-week programme is once again looking for participants, it will run online, due to the pandemic, from June 7thuntil August 27th, and will include lectures and hands-on workshops with mentors from the global data science community.
Graduates and undergraduate students, PhD students, data scientists and researchers have until January 31stto apply for the initiative which, since its inception, has seen more than 200 students spend their summers with the DSSG.
Professor Juergen Branke, Professor of Operational Research & Systems and DSSGxUK co-ordinator comments:
The 2020 DSSGxUK programme was a great success, even with the programme being carried out virtually with participants from Mexico to Romania, our partner organisations were extremely happy with what the teams produced. Just mining the data can help them achieve more with less resources, or even help argue their case with local authorities and the Government.
There are many organisations working hard to do social good who are collecting vast amounts of data in this digital age, but dont have the resources or skills to make the most of it.
The DSSG helps them unleash the potential of their data and the improvement in their services can be truly astounding.
To find out more and to apply for this years programme please visit:https://warwick.ac.uk/research/data-science/warwick-data/dssgx/
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Data Science for Social Good Programme helps Ofsted and World Bank - India Education Diary
Save 98% off the Complete Excel, VBA, and Data Science Certification Training Bundle – Neowin
Today's highlighted deal comes via our Online Courses section of the Neowin Deals store, where you can save 98% off the Complete Excel, VBA, and Data Science Certification Training Bundle. Kickstarter funded! Be the master of databases and analysis with 55 hours of beginner content on Excel, VBA, Python, Machine Learning, and more.
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Save 98% off the Complete Excel, VBA, and Data Science Certification Training Bundle - Neowin
Ilia Dub and Jasper Yip join Oliver Wyman’s Asia partnership – Consultancy.asia
Oliver Wyman has strengthened its Asian partnership with two new partners: Ilia Dub and Jasper Yip.
Effective the 1st of January 2021, Ilia Dub is a partner in Oliver Wymans Digital practice, based in Singapore. He brings over a decade of experience serving clients at the intersection of business strategy, data and technology to the partnership, with a focus on digital transformations, data management, data science and agile delivery of technology solutions.
Dub also advises CIOs and CTOs on emerging technologies such as artificial intelligence, machine learning, cloud and internet of things. In his partner role, he leads an interdisciplinary teams of consultants, designers, data scientists and software engineers working across Asia.
Based in Oliver Wymans Hong Kong office, Jasper Yip has been promoted to partner in the Financial Services practice. He covers clients across Greater China and Asia Pacific with a focus on institutions in the capital markets, wealth/asset management and fintech space.
Yips consulting experience spans strategy and business model design, digital transformation, organisation and governance design, operating model optimisation and financial management. Most recently, he supported a financial institution with the formulation of its China onshore strategy and operation plans.
In last years annual promotion round, Oliver Wyman promoted seven new partners based in Asia.
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Ilia Dub and Jasper Yip join Oliver Wyman's Asia partnership - Consultancy.asia
Poor data flows hampered governments Covid-19 response, says the Science and Technology Committee – ComputerWeekly.com
Poor data flows and a failure to capitalise on UK strengths in data science have bedevilled the governments response to the Covid-19 pandemic, a House of Commons Science and Technology Committee has found.
The committees 92-page report, The UK response to Covid-19: use of scientific advice, published 8 January, is focused on how the government has obtained and made use of scientific advice during the pandemic.
It notes that the remarkable achievement of developing and being in a position to deploy multiple vaccines against a deadly and virulent virus that was completely unknown a little over a year ago ranks as one of the most outstanding scientific accomplishments of recent years.
It recollects that the first two cases of Covid-19 were confirmed in the UK, in England, on 31 January 2020, less than a year ago. The first death from Covid-19 in the UK, in England, was announced on 5 March. As of 18 December, the total number of deaths since then, where Covid-19 is mentioned on the death certificate, is 82,624. On 06 January, another 1,041 deaths were reported.
The committee, chaired by Conservative MP Greg Clark, said in its report: A fully effective response to the pandemic has been hampered by a lack of data. For a fast-spreading, invisible, but deadly infection, data is the means of understanding and acting upon the course of the virus in the population.
The early shortage of testing capacity restricting testing only to those so ill that they were admitted to hospital had the consequence of limiting knowledge of the whereabouts of Covid-19. The ONS Infection survey did not begin until May, and the fragmentation of data across public organisations has impeded the agility and precision of the response.
The report laments the failures in data management in the governments response to the pandemic, and notes these are all the more damning given a national comparative advantage in the field.
Given the UKs strengths in statistical analysis and data science, it is regrettable that poor data flows, delays in data-sharing agreements and a general lack of structuring and data integration across both the health and social care sectors have throttled timely data sharing and analysis.
For example, it is unacceptable that detailed public health data was only made available to modellers from March. The potential consequences of this will undoubtedly include slower and less effective decision-making.
It finds solace in the establishment of the Joint Biosecurity Centre as an effort to centralise data flows to manage the pandemic, but notes it is unfortunate that no central mechanism to coordinate data was in place at the start of the pandemic.
The committee exhorts the Department of Health and Social Care (DHSC) to set out an action plan that describes what efforts have been made, and will be made, during the pandemic to address the poor data access issues raised by the scientific community and Sage [the Scientific Advisory Group for Emergencies] and its sub-groups.
This plan should, said the report, cover agreements and incentives for data sharing and data integration across the health and social care sectors and across the four nations of the UK.
The early shortage of testing capacity restricting testing only to those so ill that they were admitted to hospital had the consequence of limiting knowledge of the whereabouts of Covid-19 The Science and Technology Committee
The report points out that the line between advice and decision-making was tested on one signally important occasion, when the Prime Minister announced plans for a second stay at home order on 31 October.
Although the chief medical officer and government chief scientific adviser presented modelling data at the press conference alongside the Prime Minister, the data underlying this was only made public three days later and was subject to extensive criticism, including that the data was out of date, it added.
More positively, the report stated: The Office for National Statistics [ONS] is now conducting a very important sampling exercise in which data on the prevalence of Covid-19 in the UK population will be gathered and reported twice-weekly.
It is of great importance in providing data on the spread of diseases, its impact on the different demographic groups and geographies, the incidence of asymptomatic transmission and even the reproduction or R number which the government has made key to easing some social distancing restrictions.
In evidence to the committee, the national statistician, Ian Diamond, gave an impressive account of the speed in which his team had been able to organise and implement a significant testing programme.
The report quotes Diamond as having said: The fact that we came into it on a Thursday and, with the University of Oxford, put together the design and protocoland put it to medical ethics the following Monday and data ethics on Tuesday, with letters out to potential participants on the Wednesday, seems to me to be one of the most rapid surveys I have ever in my life seen go into the field.
However, he also told the committee that the request to put together such a testing programme was made only on 17 April 2020.
It was also drawn to the committees attention that data on the ethnicity of those dying from Covid-19 was not systematically collected.
The committee is recommending that government should consider how ethnicity data on those dying as a result of Covid-19 could be systematically recorded, and it notes that there are significant unexplained differences in the death rates in the UK of Black, Asian and minority ethnic [BAME] groups compared to the population as a whole.
The report also brings out a structural over-emphasis on epidemiological data, as opposed to broader data about the impact of the pandemic on the economy, mental health and other areas.
The report adduces public comments made by Mark Woolhouse, a professor and one of the epidemiologists advising the Scientific Pandemic Influenza Group on Modelling (SPI-M) and the Scottish Government Covid-19 Advisory Group, that he thought scientific advice was driven far too much by epidemiology.
Speaking to the committee in June, Woolhouse said: In the early stages of the epidemic, before we had large amounts of [public health] data, [advice] was largely on the basis of modelling, and that is all right and proper and as it should be, but we are looking literally at only one side of the equation when we do that.
He suggested, according to the report, that the other side of the equation included the harms done by lockdown, including impacts on mental health and social wellbeing, the education of our children, and our economy.
The report noted: While the experience of no country is perfectly comparable with others, it will be important to understand the reasons for [comparatively poor performance in relation to peer nations] to learn lessons for the future.
In this report, there are questions of how quickly scientific analysis could be translated into government decisions; whether full advantage had been taken of learning from the experience of other countries; and the extent to which scientific advice took as a given operational constraints, such as testing capacity, or sought to change them.
For any emergency situation, data systems need to be in place up front to be able to give the information to make the analysis and make the decisions Patrick Vallance, Government Office for Science
Patrick Vallance, the governments chief scientific adviser, told the committee, in registering the importance of data: One lesson that is very important to learn from this pandemic, and for emergencies in general, is that data flows and data systems are incredibly important. You need the information to be able to make the decisions. Therefore, for any emergency situation, those data systems need to be in place up front to be able to give the information to make the analysis and make the decisions.
He told the committee that this was not limited to testing data, but also encompassed basic information flows around patients in hospital, rates of admission and rates of movement.
The report added that Vallance suggested that a principal issue in managing the pandemic was that at the beginning, there were definitely times when we would have liked data that was difficult to getdata flows are getting much better now, but the NHS does not have centralised data flows on everything you need.
As an example, comprehensive data on Covid-19 in care homes were not available to the government in the early months of the pandemic. At a Sage meeting on 15 March, it was noted that because of a 5 to 7 day lag in data provision for modelling, Sage now believes there are more cases in the UK than Sage previously expected at this point, and we may therefore be further ahead on the epidemic curve.
The committee is calling on the government to publish the advice it has received on indirect effects of Covid-19 (including impacts on mental health and social wellbeing, education and the economy) and work to improve transparency around the operation of the Joint Biosecurity Centre.
Measures taken to contain the pandemic [have] had wider and indirect effects, such as on peoples livelihoods, educational progress and mental and emotional wellbeing, said the committee.
The assessment of these wider impacts was and remains much less transparent than the epidemiological analysis; the people conducting the analysis and giving advice are less visible than epidemiological modelling advisers; and its role in decision-making opaque.
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Healthcare Innovations: Predictions for 2021 Based on the Viewpoints of Analytics Thought Leaders and Industry Experts | Quantzig – Business Wire
LONDON--(BUSINESS WIRE)--Quantzig, a leader in delivering scalable analytics solutions and data science services, announced the completion of its recent article that unravels the healthcare innovations set to transform the healthcare industry in 2021.
The use of technology in healthcare skyrocketed in 2020 as hospitals, health systems, and patients increasingly relied on digital health technologies for care delivery during the pandemic, setting the stage for continued growth and innovation. With several new healthcare innovations paving their way into the health-tech landscape, analytics thought leaders at Quantzig got out their crystal balls to predict and share their views on the most promising healthcare innovations and medical breakthroughs impacting the healthcare industry in 2021 and beyond.
With COVID-19 vaccination trials rolling out this year, next-gen solutions for patient monitoring and virtual healthcare will witness high demand in 2021, says an analytics expert at Quantzig.
Partnering with Quantzig can help you adopt a progressive approach to innovation, with continuous guidance and support from analytics and healthcare industry experts. Request a FREE proposal to get started.
Key highlights-
2021 will witness innovations transforming how healthcare researchers aggregate and analyze big data, making data a powerful tool for drug development, lifestyle studies, and research
With the proliferation of advanced technologies, it is now possible for businesses to leverage the power of AI and ML to gain a leading edge
Quantzig is at the forefront of enabling healthcare innovation to drive better healthcare outcomes and improved patient experiences. Contact us to learn more about how you can benefit by focusing on tech-driven innovations.
Innovation is key to drive growth and profitability across sectors, and healthcare is no exception. But implementing new, innovative technologies can be challenging from a technical standpoint. However, the need of the hour is to strengthen your understanding and leverage technology to drive outcomes and offer personalized experiences for patients across the healthcare continuum. Though the benefits of healthcare innovations are widespread, building the necessary skills and capabilities to identify and capitalize on them is not an easy task. At Quantzig, we suggest adopting a progressive approach with guidance and support from big data and analytics experts to test and find loopholes prior to organization-wide implementation. Request more information from our experts to find out how we can help you.
Healthcare Innovations That Will Transform Healthcare in 2021
Few of these healthcare innovations have been a transformative force in reshaping and disrupting the healthcare industry in the past. As such, the new healthcare innovations hold tremendous potential in driving future healthcare outcomes by delivering a personalized, spontaneous, and cohesive experience to both payers and providers in the healthcare ecosystem. Quantzigs team of 550+ seasoned analytics experts and data science professionals have the expertise and skill it takes to design and build systems tailored to the particular needs of your business and equip you with data-driven, actionable insights for prudent decision-making. Request a FREE pilot project to learn more about our proprietary analytics platforms and core capabilities.
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About Quantzig
Quantzig is the world's foremost full-service advanced analytics and business intelligence solution provider, turning clients' complex, unstructured data into intelligent, actionable insights that enable them to solve complex business problems and inspire innovation, change, and growth.
Over the past 16 years, our insights have helped over 120 clients spanning across industries and sectors like Pharmaceutical and Life Sciences, Retail and CPG, Food and Beverage, and more. We have successfully delivered 1500 in-depth solutions in areas like Marketing Analytics, Customer Analytics, Supply Chain Analytics, and more. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal.
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