Leads Analytics projects within the Analytics ContinuumConceptualizes and builds predictive modeling, simulations, and optimization solutions to address business questions or use casesApplies ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the businessConducts model validations and continuous improvement of the algorithms, capabilities, or solutions builtYou 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)
Skills Required
Logistic Regression, Predictive Modeling, Forecasting, Business Inteligence, Business Analytics, Sql