
Data Science Leader
7 days ago
This role involves collaborating with cross-functional teams to derive business value from data, leveraging expertise in machine learning, statistical modeling, and data visualization.
Key Responsibilities:
- Analyze investor behavior and distribution partner data to identify trends and opportunities, developing models for investor segmentation, churn prediction, and customer lifetime value estimation.
- Measure campaign effectiveness, optimize targeting strategies, and enhance personalization, supporting 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, designing dashboards and reports in collaboration with the MIS team to provide actionable insights.
- Ensure data accuracy, security, and compliance with regulatory requirements.
Required Skills and Qualifications:
- 6-8 years of experience in data science, analytics, or risk modeling in the financial services sector (mutual funds, banking, lending).
- Excellent skills in Advanced 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.
Essential Knowledge:
- A strong understanding of investor behavior, digital customer journeys, and financial product analytics.
- Hands-on experience in automating data pipelines, web scraping, and predictive analytics.
- The ability to translate complex data insights into clear business strategies.
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