As a Data Scientist you will apply strong expertise through the use of machine learning data mining and information retrieval to design prototype and build next generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
Key Responsibilities
- Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
- Develop test and deploy data science solutions using Python SQL and PySpark on enterprise platforms such as Databricks.
- Collaborate with data scientists to translate models into production-ready code.
- Implement CI/CD pipelines and manage code repositories using GitHub Enterprise.
- Design and optimize mathematical programming and machine learning models for real-world applications like Incentive elasticity model.
- Expereince implementing scenario simulation algorithms.
- Work independently to break down complex problems into actionable development tasks.
- Ensure code quality scalability and maintainability in a production environment.
- Contribute to sprint planning documentation and cross-functional collaboration.
- Collaborate coach and learn with a growing team of experienced Data Scientists.
- Stay connected with external sources of ideas through conferences and community engagements
Requirements
- 8 years of experience working as a Data Scientist
- Hands-on experience with enterprise data science solutions preferably in retail inventory management or operations research.
- Proficiency in Python SQL and PySpark.
- Experience with Databricks or similar enterprise cloud environments.
- Experience with production-level coding and deployment practices.
- Familiarity with basic machine learning techniques and mathematical optimization methods.
- Proficient in data science libraries and ML pipelines such as; NumPy SciPy scikit-learn MLlib PyTorch TensorFlow.
- Should have experience working on Price Elasticity.
- Self-starter with an ownership mindset and the ability to work with minimal supervision.