Develop advanced SQL queries and data models for portfolio analysis, client segmentation and reporting
Apply data discovery to find critical data assets and map them to wealth management processes
Execute data classification frameworks for sensitive and confidential information
Create predictive and descriptive models for investment decisions, client retention and cross-sell
Mentor junior data practitioners on SQL modeling and privacy-aware analytics
From the employer’s posting
Develop advanced SQL queries and data models that optimize portfolio analysis client segmentation and performance reporting
Apply data discovery techniques to identify critical data assets across structured and unstructured sources and map them to key wealth management business processes
Execute data classification frameworks that categorize sensitive and confidential information
Create predictive and descriptive models that enhance investment decisions client retention and cross sell opportunities
Mentor junior data practitioners on best practices in SQL modeling privacy aware analytics and domain nuances
Tools in this posting
SQL
Source — Tool mentions in context
This hybrid day shift position requires deep expertise in SQL data discovery and classification with strong domain experience in asset and wealth management to drive compliant insights and strategic decision making across the enterprise.
Required Skills : Technical Skills: SQL Data Privacy Discovery Classification Data Discovery Domain Skills:Asset & Wealth Management 5.
Responsibilities : -Design and implement scalable analytics solutions that harness complex asset and wealth management datasets to deliver clear business insights while maintaining rigorous data privacy safeguards -Develop advanced SQL queries and data models that optimize portfolio analysis client segmentation and performance reporting for multiple asset classes in a hybrid work setup -Apply data discovery techniques to identify critical data assets across structured and unstructured sources and map them to key wealth management business processes -Execute data classification frameworks that categorize sensitive and confidential information to support compliant analytics and responsible data usage across global teams -Collaborate with portfolio managers risk specialists and operations teams to translate investment and client service questions into robust data science solutions with measurable outcomes -Create predictive and descriptive models that enhance investment decisions client retention and cross sell opportunities while embedding privacy by design principles into each solution -Establish repeatable data quality checks and validation routines that strengthen the reliability of risk metrics performance indicators and regulatory reports used in asset and wealth management -Document data lineage usage patterns and privacy controls that clarify how information flows through analytical pipelines and support audit readiness for internal and external reviews -Partner with information security and compliance experts to align data discovery and classification practices with evolving regulations and firm policies ensuring resilient protection of client information -Guide the integration of new data sources into analytic platforms by assessing data sensitivity access needs and fit for purpose within wealth management strategies -Mentor junior data practitioners on best practices in SQL modeling privacy aware analytics and domain nuances so that team output remains consistent and high quality -Communicate findings through clear narratives and visual summaries that help business stakeholders understand drivers of performance and the privacy implications of proposed actions -Continuously refine analytic approaches by monitoring model performance feedback and changes in market conditions to keep insights relevant and aligned with organizational objectives and societal trust in financial services -Qualifications -Demonstrate extensive hands on experience using SQL to design complex queries data transformations and performance optimized models within large scale financial data environments -Exhibit deep familiarity with data privacy principles regulations and control mechanisms that govern the handling of client and transaction information in asset and wealth management contexts -Show strong capability in data discovery methods and tools enabling accurate identification of critical data elements and sources required for investment analytics and regulatory reporting -Apply structured data classification methodologies that distinguish sensitive confidential and operational data in support of secure analytics and compliant information sharing -Bring solid domain expertise in asset and wealth management including understanding of portfolios investment products client profiling risk measures and associated reporting practices -Display experience working in hybrid teams using collaborative platforms and version control practices to manage analytic assets and documentation across geographies -Demonstrate ability to design and deploy statistical or machine learning models that create tangible improvements in investment insights operational efficiency or client engagement metrics -Illustrate strong problem solving skills and communication abilities to engage with nontechnical stakeholders clarify complex findings and influence decisions with data driven arguments -Show a track record of adhering to organizational governance frameworks data standards and quality benchmarks that ensure analytic outputs remain accurate trusted and reusable 9.
Yes. We’ve followed 3 other Data Scientist jobs there since August 2026. All 3 are still up.
BengaluruStill up after 90 days, first seen Aug 11
BengaluruStill up after 38 days, first seen Oct 2
ChennaiStill up after 7 days, first seen Nov 3
This jobUp 5 days so far, first seen Nov 4
Aug 11Today
Large employers often post one title for several teams, so these can be separate openings.
About Cognizant
People
About 351,600 in 2025, up 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as CTSH.
H-1B visas
1,401 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
1. Job Title : Data Scientist 2. Job Summary : Data Scientist role in a global asset and wealth management organization focused on designing and executing advanced analytics solutions that safeguard data privacy while improving client outcomes and operational efficiency. This hybrid day shift position requires deep expertise in SQL data discovery and classification with strong domain experience in asset and wealth management to drive compliant insights and strategic decision making across the enterprise. 3. Experience : 8 - 12 years 4. Required Skills : Technical Skills: SQL Data Privacy Discovery Classification Data Discovery Domain Skills:Asset & Wealth Management 5. Nice to have skills : Domain Skills: 6. Technology : Custom Service 7. Shift : Day 8. Responsibilities : -Design and implement scalable analytics solutions that harness complex asset and wealth management datasets to deliver clear business insights while maintaining rigorous data privacy safeguards -Develop advanced SQL queries and data models that optimize portfolio analysis client segmentation and performance reporting for multiple asset classes in a hybrid work setup -Apply data discovery techniques to identify critical data assets across structured and unstructured sources and map them to key wealth management business processes -Execute data classification frameworks that categorize sensitive and confidential information to support compliant analytics and responsible data usage across global teams -Collaborate with portfolio managers risk specialists and operations teams to translate investment and client service questions into robust data science solutions with measurable outcomes -Create predictive and descriptive models that enhance investment decisions client retention and cross sell opportunities while embedding privacy by design principles into each solution -Establish repeatable data quality checks and validation routines that strengthen the reliability of risk metrics performance indicators and regulatory reports used in asset and wealth management -Document data lineage usage patterns and privacy controls that clarify how information flows through analytical pipelines and support audit readiness for internal and external reviews -Partner with information security and compliance experts to align data discovery and classification practices with evolving regulations and firm policies ensuring resilient protection of client information -Guide the integration of new data sources into analytic platforms by assessing data sensitivity access needs and fit for purpose within wealth management strategies -Mentor junior data practitioners on best practices in SQL modeling privacy aware analytics and domain nuances so that team output remains consistent and high quality -Communicate findings through clear narratives and visual summaries that help business stakeholders understand drivers of performance and the privacy implications of proposed actions -Continuously refine analytic approaches by monitoring model performance feedback and changes in market conditions to keep insights relevant and aligned with organizational objectives and societal trust in financial services -Qualifications -Demonstrate extensive hands on experience using SQL to design complex queries data transformations and performance optimized models within large scale financial data environments -Exhibit deep familiarity with data privacy principles regulations and control mechanisms that govern the handling of client and transaction information in asset and wealth management contexts -Show strong capability in data discovery methods and tools enabling accurate identification of critical data elements and sources required for investment analytics and regulatory reporting -Apply structured data classification methodologies that distinguish sensitive confidential and operational data in support of secure analytics and compliant information sharing -Bring solid domain expertise in asset and wealth management including understanding of portfolios investment products client profiling risk measures and associated reporting practices -Display experience working in hybrid teams using collaborative platforms and version control practices to manage analytic assets and documentation across geographies -Demonstrate ability to design and deploy statistical or machine learning models that create tangible improvements in investment insights operational efficiency or client engagement metrics -Illustrate strong problem solving skills and communication abilities to engage with nontechnical stakeholders clarify complex findings and influence decisions with data driven arguments -Show a track record of adhering to organizational governance frameworks data standards and quality benchmarks that ensure analytic outputs remain accurate trusted and reusable 9. Job Location : Primary Location :INTSHYDA02(ITIND Madhapur Bld 12A (MDH) SEZ) Alternate Location :INWBKOLA01(ITIND Technocomplex (TCX) STPI) Alternate Location 1 :NA NA 10. Job Type : Sr. Associate - Projects [60PM00] 11. Demand Requires Travel? : No 12. Certifications Required : NA