▷ Apply in 3 Minutes Data Scientist
3 weeks ago
We are looking for a Data Scientist who is passionate about deriving business value from data. In this role, you will work closely with our Digital, Marketing, Analytics, Operations teams to analyze investor and partner data, build predictive models, The ideal candidate should have experience in machine learning, statistical modeling, and data visualization, with a strong understanding of financial services, customer behavior analytics, and risk modelling.
Responsibilities
Analyze investor behaviour and distribution partner data to uncover trends and opportunities. Develop models for investor segmentation, churn prediction, and customer lifetime value estimation.
Measure campaign effectiveness, optimize targeting strategies, and enhance personalization. Support the team with automation, early warning signals, and fraud detection models.
Implement text mining and sentiment analysis on investor feedback, social media, and complaint data. Design dashboards and reports in collaboration with the MIS team to provide actionable insights.
Ensure data accuracy, security, and compliance with regulatory requirements.
Experience
6-8 years
Excellent in Advance Excel.
Programming knowledge of Python, R, SAS (Enterprise Guide, E-Miner, VIYA)
Databases: SQL Server, MongoDB
Visualization: R-Shiny, Power BI, Excel
Machine Learning & Statistical Techniques. Regression ( Linear, Logistic)
Good to have ensemble methods: Random Forest, Gradient Boosting, NLP & Text Mining-Sentiment Analysis, Fuzzy, String Matching etc
Knowledge
6+ years of experience in data science, analytics, or risk modeling in the financial services sector (mutual funds,
banking, lending).
Experience building Investor behavior models, early warning systems, and propensity model.
Strong understanding of investor behavior, digital customer journeys, and financial product analytics
Hands-on experience in automating data pipelines, web scraping, and predictive analytics.
Ability to translate complex data insights into clear business strategies
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