Senior Data Scientist at NielsenIQ

Vadodara, gujarat, India -

Full Time

Start Date

Immediate

Expiry Date

11 Aug, 26

Salary

0.0

Posted On

13 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Statistical Analysis, Python, Deep Learning, Time Series, Sampling, Geospatial Data, Git, Bitbucket, Data Mining, Universe Estimation, R&D, FMCG Industry Knowledge, RMS Systems, Large-scale Databases, Communication

Industry

Software Development

Description

Job Description About the job You will work with a global team dedicated to the development of new methodologies for Retail Establishment Survey & other data collection processes. We are looking for someone in our methods team to be part of these transformational initiatives to improve quality and redefine the process of RES design and Universe Estimation leveraging advanced technologies, integration of data sources, Machine Learning techniques, statistical and data analytical skills. You should have a passion for innovation, Research & Development and challenging data opportunities! Responsibilities Own & lead evaluating & improvising the methodologies developed to improve quality of RES Designs and transforming Universe Estimation process involving Machine Learning & Statistical techniques. Research new methodologies, research directions and quantify their improvement Deliver methodological enhancements improving overall quality & process efficiencies. Work closely with different teams such as technology, other Data Science teams, internal stakeholders during development & deployment of new methodologies. Prototype as well as support pilot programs to drive innovation. Owns and maintains Data Science global methodologies and ensures they are well documented and understood. Asks questions to engage & motivate team on seeking further understanding of data. Reviews the progress of projects and POCs and proposes improvements and constructive critiques. Qualifications Master’s / Doctorate Degree in Data Science, Mathematics, Statistics or Engineering degree in Computer Science, Data Science or related fields involving statistical analysis of large data sets At least 5 years’ of relevant experience Exhibits a solid understanding of FMCG Industry for specific core process and Advanced knowledge of RMS systems/products. Experience in designing studies/sampling Comfortable designing solutions and supporting a team to execute Displays innovative thinking, data analytical skills, application of statistical techniques and encourages. experimentation in delivery of work. Can support others to understand and apply more complicated technical principles & methodologies, creating clarity and focus for teams to deliver. Domain expert knowledge of the following: programming, statistical analysis / machine learning/deep learning, time series, sampling Experienced in Python programming, machine learning and working with queries and large-scale databases Preferable knowledge of geospatial data and techniques Able to work in virtual environment and familiar with git/Bitbucket processes Drive to continuously learn and adopt new technologies and tools Strong communication, presentation and collaboration skills Additional Information Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies. About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion

Responsibilities

Lead the evaluation and improvement of methodologies for Retail Establishment Survey designs and Universe Estimation using Machine Learning and statistical techniques. Collaborate with global technology and data science teams to prototype, document, and deploy methodological enhancements.