SENIOR DATA SCIENTIST, GLOBAL DATA SCIENCE

Responsibilities:

1. Conceptualizes and builds predictive modeling, simulations, and optimization solutions to address business questions or use cases
2. Applies ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the business
3. Develops end to end business solutions from data extraction, data preparation, data mining to statistical modeling and then building business presentations
4. Conducts model validations and continuous improvement of the algorithms, capabilities, or solutions built
5. Deploys models using Airflow, Docker on Google Cloud Platforms
6. Own Pricing and Promotion, Marketing Mix from scoping to delivery
7. Study large amounts of data to discover trends and patterns Mine data through various technologies like BigQuery and SQL
8. Present insights in an easy to interpret way to the business teams
9. Develop visualization (e.g. Looker, PyDash, Flask, PlotLy, streamlit) using large datasets and model output datasets
10. Ready to work closely with business partners across geographies

Required Qualifications:

1. BE/BTECH [ Computer Science, Information Technology is preferred ], MBA or PGDM in Business Analytics / Data Science, Additional DS Certifications or Courses, MSC / MSTAT in Economics or Statistics
2. 5+ years of experience in building statistical models and driving insights
3. Hands-on/experience on developing statistical models, such as linear regression, ridge regression, lasso, random forest, SVM, gradient boosting, logistic regression, K-Means Clustering, Hierarchical Clustering, Bayesian Regression etc.
4. Hands on experience on coding languages Python(mandatory) and SQL
5. Knowledge of using GitHub, Airflow for coding and model deployments
6. Understand visualization frameworks PyDash, Flask, PlotLy
7. Strong Understanding of Cloud Frameworks Google Cloud, Snowflake and services like Kubernetes, Cloud Build Cloud Run.
8. Experience front facing Business teams (Client facing role) supporting and working with multi-functional teams in a dynamic environment

Preferred Qualifications:

1. Managing, transforming, and developing statistical models for RGM/Pricing and/or Marketing Mix Models
2. Experience with third-party data i.e., syndicated market data, Point of Sales, etc.
3. Working knowledge of consumer packaged goods industry
4. Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
5. Knowledge of Google Cloud products (BigQuery, data studio, kubernetes, cloud build, cloud run etc)
6. Knowledge of deployment of models in Cloud Environment using Airflow, Docker