Chief Data Analytics Officer

1 week ago

Gulbarga, Karnataka, India beBeeDataStrategist Full time ₹ 12,00,000 - ₹ 18,00,000

Job Overview

We are seeking a seasoned Data Strategist to lead our data-driven initiatives.

This role involves collaborating with cross-functional teams to uncover insights from investor and partner data, developing predictive models, and implementing data visualization solutions. The ideal candidate will have experience in machine learning, statistical modeling, and data visualization, with a strong understanding of financial services, customer behavior analytics, and risk management.

Responsibilities:

  • Uncover trends and opportunities by analyzing investor behaviour and distribution partner data. 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.

Requirements:

  • 8-10 years of experience in data science, analytics, or risk modeling in the financial services sector.
  • Advanced skills in 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.

Desirable Skills:

  • 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 behaviour, 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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