Assistant Manager, Business Analytics

• Leads Analytics projects within the Analytics Continuum
• Conceptualizes and builds predictive modeling, simulations, and optimization solutions to address business questions or use cases
• Applies ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the business
• Conducts model validations and continuous improvement of the algorithms, capabilities, or solutions built

You connect the dots -

• Drive insights from internal and external data for business
• Assemble large, sophisticated data sets that meet functional / non-functional business requirements
• Build data and visualization tools for Business analytics to assist them in decision making

You are a collaborator -

• Work closely with Division Analytics team leads
• Work with data and analytics specialists across functions to drive data solutions

You are an innovator -

• Identify, design, and implement new algorithms, process improvements: while continuously automating processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Qualifications

What you'll need

• Graduation/Masters in Statistics/ Applied Mathematics/ Computer Science
• 1+ years of experience in building data models and driving insights
• Hands-on/experience on developing statistical models, such as regression, ridge regression, lasso, random forest, SVM, gradient boosting, logistic regression, K-Means Clustering, Hierarchical Clustering etc.
• Hands on experience on coding languages Python(mandatory), R, SQL, PySpark, SparkR
• Knowledge of using GitHub, Airflow for coding and model executions
• Handling, redefining, developing statistical models for RGM/Pricing and/or Marketing Efficiency and communicating insights decks to business
• Validated understanding on tools like Tableau, Domo, Power BI and web apps framework using plotly, pydash, sql
• Experience front facing Business teams (Client facing role) supporting and working with multi-functional teams in a dynamic environment

What you'll need (Preferred)

• Experience with third-party data i.e., syndicated market data, Point of Sales, etc.
• Shown understanding of consumer packaged goods industry
• Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience visualizing/communicating data for partners using: Tableau, DOMO, pydash, plotly, d3.js, ggplot2, pydash, R Shiny etc
• Willingness and ability to experiment with new tools and techniques
• Good facilitation and project management skills
• Ability to maintain personal composure and thoughtfully handle difficult situations.
• Knowledge of Google products (BigQuery, data studio, colab, Google Slides, Google Sheets etc)