Data Scientist, Principal

About the Role

Key Responsibilities

• Build a high-performance team of data scientists and analysts capable of gathering and synthesizing data quickly and accurately through predictive and forecasting models.
• Forge strong partnerships with business and technology leaders and provide thought leadership on various data science projects and strategic plans.
• Be a hands-on leader that drives development of models for demand sensing/forecasting, market intelligence, revenue management, simulation, and stochastic models.
• Own end-to-end discovery, design, configuration, testing, and deployment of analytical models and communicate with internal and external stakeholders.
• Identify relevant internal and external data sources, and recommend and oversee appropriate statistical, machine learning, and predictive modeling concepts.
• Apply a variety of machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimizations) to derive insights and evaluate their advantages and drawbacks.
• Use the latest advancements in AI/ML to solve complex business problems.
• Collaborate with clients, project management, solution architects, consultants, and data engineers to ensure successful project delivery.
• Guide data scientists and oversee their activities to ensure proper alignment, execution, and adherence to high coding standards and best practices.

Requirements

• 8+ years of experience in Data Science and Analytics with a proven track record as a lead data scientist.
• PhD preferred in fields such as Operations Research, Mathematics, Science, Engineering, Business Administration, Business Analytics, Computer Science, or related fields.
• Strong programming skills in Python and/or R for Data Science.
• Proficiency in analytical techniques, data mining, and handling large datasets.
• Deep knowledge of statistical and machine learning algorithms.
• Experience in applied analytical methods in supply chain and planning, including demand planning, supply planning, market intelligence, and inventory management.
• Strong presentation and communication skills to convey complex technical concepts to non-technical audiences.
• Experience with SQL, databases, and big data technologies like Hadoop, Hive, and Spark.
• Preferable experience with Deep Learning frameworks such as Keras, TensorFlow, or PyTorch.

Nice to Have

• Experience with Deep Learning frameworks such as Keras, TensorFlow, or PyTorch.

Qualifications

• Doctoral degree (PhD) in relevant fields or equivalent experience.

Benefits & Perks

• Annual salary range of $158,141-$217,444.
• Eligibility to participate in medical, retirement, and other company-sponsored benefits.