Sr. Data Scientist

7 days ago

Gurgaon, Haryana, India Itech Enterprises Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Must Have Skills:

  • Python / R
  • Experience in risk scorecards, predictive modelling, machine learning.
  • Experience in Univariate and Multivariate Regression, Generalized Regression Modelling, Time series forecasting.

Key Results Areas

  • Data mining and identification of trends
  • Communication of trends and insights to stakeholders
  • Development of scorecards & predictive models

Responsibilities

  • understand a business problem & translate into statistical one is a must.
  • He/she should be able to decide on the best modeling/analysis techniques and provide actionable insights/ model algorithms to the business.

Model development & Deep-dive Strategic Analysis:

  • Data extraction: Extract data from appropriate sources. Require knowledge of databases.
  • Data processing: Perform complex data processing (e.g. merging, sorting, data transformations).
  • Profiling and analysis: Combine in-depth business knowledge, insights, and techniques such as data visualization, cross-tabs, statistical tests, and data mining techniques to identify risk segments, behavioral trends, product preferences, up-selling, cross-selling, and retention opportunities
  • Model development: Apply standard and cutting-edge techniques (statistical modeling, data mining, predictive analytics, machine learning, optimization) to identify drivers of a business metric. Compare techniques using validation to arrive at the best model.

Model scoring and business applications of modeling/analytics:

  • Insert developed models into the scoring process
  • Improvise the models based on feedbacks from scoring process

Communication, Coordination & Presentation:

  • Work with a consultative mindset to gather requirements from other team professionals to identify the right requirements.

Skills:

  • Extensive experience of statistical tools e.g. R, Python, VBA, Excel etc.
  • Experience in statistical modelling using Univariate and Multivariate Regression, Generalized Regression Modelling, Time series forecasting, Non-Parametric methods, Logistic Regression, Survival Analysis, Factor Analysis, Clustering, CART, Decision Trees, CHAID, Linear Optimization, Hypothesis testing, Boosting Techniques, Factor Analysis, Scorecard Development etc
  • Experience in risk scorecards, predictive modelling, machine learning etc.
  • Ability to extract data from databases, clean and prepare for modelling.

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