Responsibilities

1. Build and develop analytical models using machine learning & AI, working alongside a strong team of Leads, Analysts, Architects to deliver priority outcomes in alignment with the strategic roadmap for Industry Solutions business unit
2. Act as the technical mentor for other data scientists ensuring optimal solutioning for business problem at hand. Create and manage standards, processes, and procedures to ensure agile delivery and consistent operations.
3. Act as an evangelist and catalyst for Advanced Analytics innovation
4. Manage the portfolio of work for Advanced Analytics and partner with stakeholders on monthly governance
5. Partner on a robust, sustainable cloud first big data architecture, data lake, data mart and other assorted reporting/distribution services with the data engineering teams
6. Attract, develop, retain talent and improving productivity, efficiency and effectiveness of the team and / or business.

Qualifications

• • Experience in full development lifecycle of an Analytics platform especially in context of solving problems for a business function
  • Statistics – Basic probability distributions, estimation techniques, confidence intervals, hypothesis testing (z-test, t-test, ANOVA etc.). Understanding of Maximum Likelihood Estimation is a plus
  • Machine Learning – Regression, Classification, Clustering, Data preparation (outlier treatment, missing value imputations etc.), Feature engineering (polynomial, log and other functional transformations), Feature selection, Time series, Text Mining & Model interpretation through Decision Trees, Linear Models
  • Programming – Hands-on in R/Python and experience in using different Statistics/ML libraries available (rpart, c5.0, random forests, GLM, GBM, Scikit-learn etc.)
  • Data engineering – Hands-on in SQL and experienced in working with RDBMS for data extraction and data read/write. Understanding of Data Warehouse fundamentals (architectural layers & schema types) is a plus
  • Data Visualization – Experience in one or more Data Visualization tools (MS Power BI, Tableau etc.)

  The candidate must also have:

  • Masters in Statistics/Econometrics or PhD in Statistics/Economics/Computer Science or related discipline is preferable, but a candidate with MS combined with strong analytical background in problems relating to Big Data and Analytics is also acceptable.
  • Excellent written and oral communication skills, particularly the ability to synthesize complex issues/scenarios into easy-to-understand concepts.
  • An attention to detail with self-discipline and a drive for results.
  • Demonstrated ability to work in ambiguous situations and across organizational boundaries.