Leading Business Insights through Data Driven Strategies

18 hours ago

Davangere, Karnataka, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,01,00,000

Unlock Business Potential as a Data Scientist

Job Description:

The role of a Data Scientist is pivotal in uncovering hidden business value from data.

To excel in this position, you will collaborate closely with cross-functional teams to drive informed business decisions through data-driven insights.

  • Analyze investor behavior and distribution partner data to identify trends and opportunities.
  • Develop predictive models for investor segmentation, churn prediction, and customer lifetime value estimation.
  • Evaluate campaign effectiveness, optimize targeting strategies, and enhance personalization.
  • Support the team with automation, early warning signals, and fraud detection models.

Key Responsibilities:

  1. Investor Behavior Analysis: Uncover investor behavior and distribution partner data to gain valuable insights.
  2. Model Development: Create predictive models for investor segmentation, churn prediction, and customer lifetime value estimation.
  3. Campaign Effectiveness: Assess campaign effectiveness, refine targeting strategies, and boost personalization.
  4. Automation and Support: Collaborate on automation, early warning signals, and fraud detection models.

Essential Skills and Qualifications:

  • 6-8 years of experience in data science, analytics, or risk modeling in the financial services sector.
  • Proficient knowledge of Advanced Excel.
  • Programming skills in Python, R, SAS (Enterprise Guide, E-Miner, VIYA).
  • Familiarity with databases: SQL Server, MongoDB.
  • Experience with visualization tools: R-Shiny, Power BI, Excel.
  • Strong understanding of machine learning & statistical techniques: Regression (Linear, Logistic), Ensemble methods (Random Forest, Gradient Boosting), NLP & Text Mining-Sentiment Analysis.

Desirable Skills and Experience:

  • Hands-on experience building Investor behavior models, early warning systems, and propensity models.
  • In-depth understanding of investor behavior, digital customer journeys, and financial product analytics.
  • Ability to automate data pipelines, web scraping, and predictive analytics.
  • Capacity to distill complex data insights into clear business strategies.

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