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Mid-level, popular Data Scientist title with broad ML and cloud requirements at a recognizable employer increases competition.
Strong preference for retail/CPG forecasting experience makes cross-industry transferability limited.
Explicit 3+ years plus mandatory PySpark, Databricks, cloud, and retail forecasting experience makes shortlisting stringent.
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Design, optimize, and maintain scalable ETL and ML/AI pipelines using PySpark, Databricks, and cloud platforms (Azure/GCP) focused on retail/CPG demand forecasting and supply chain use cases.
Develop automated data quality checks and optimize cloud resource allocation to manage costs effectively.
Collaborate with business stakeholders and cross-functional teams to understand requirements, explain model performance, and implement analytics and optimization solutions impacting merchandising, replenishment, and forecasting.
Master’s degree in engineering, computer science, data science, operations research, statistics, mathematics, or quantitative sciences, or relevant work experience.
3+ years experience in Data Science or Data Engineering with a focus on full lifecycle demand forecasting or time-series modeling projects, including production deployment and performance management.
Strong hands-on experience with Python/PySpark, SQL, relational or NoSQL databases, cloud environments (AWS, Azure, GCP), and orchestration tools like Databricks or Airflow.
Experience designing and operating production demand forecasting systems using statistical time-series methods and regression approaches, with proven communication skills to present technical analysis to business stakeholders.
Experienced in retail or CPG demand forecasting, promotional planning, or supply-chain analytics, ideally with direct interaction with merchant, replenishment, or supply-chain stakeholders.
Capable of managing end-to-end production-grade data and ML pipelines including feature engineering, model training/scoring, and forecast consumption by downstream systems.
Comfortable working independently in a fast-paced, innovative environment, with ability to learn new technologies quickly and communicate complex technical topics effectively to non-technical stakeholders.