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 Git Hub, 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 (Big Query, data studio, colab, Google Slides, Google Sheets etc)