Senior Data Scientist

We are looking for experienced and visionary Senior Data Scientist to join our client’s advanced research and development team. Our customer is a global leader in industry, worker safety, and consumer goods. Headquartered in Maplewood, Minnesota, the company produces over 60,000 innovative products, spanning adhesives, abrasives, laminates, personal protective equipment, window films, paint protection film, electrical and electronic components, car-care products, electronic circuits, and optical films.

In this role, you will lead the design, development, and deployment of cutting-edge machine learning models and statistical algorithms to solve some of the company’s most complex business challenges. You will apply your deep expertise in statistical computing, natural language processing, and reinforcement learning to create real-world systems that deliver measurable value.

As a senior team member, you will also shape technical strategy, mentor colleagues, and foster a culture of rigorous experimentation and data-driven excellence, ensuring that innovation translates into tangible impact across the organization. 

Requirements:

• A Master’s or PhD in Statistics, Applied Mathematics, Machine Learning, Computer Science, or a related quantitative field.
• 5+ years of hands-on experience designing and implementing statistical computing, NLP, and/or reinforcement learning algorithms for real-world systems.
• Strong theoretical and practical background in statistical computing, including experimental design, fractional factorial and response surface methodology, and multi-objective optimization.
• Expert-level proficiency in Python and its core data science libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
• Proven experience in synthetic data generation, including stochastic process simulations.
• Excellent problem-solving abilities with a creative and analytical mindset.
• Strong communication and collaboration skills, with a proven ability to present complex results to diverse audiences and thrive in a fast-paced R&D environment.

Preferred Qualifications & Skills:

• Industry experience in Consumer Packaged Goods (CPG) or a related field.
• Experience contributing to or developing enterprise data stores (e.g., data meshes, lakehouses).
• Knowledge of MLOps, DevOps methodologies, and CI/CD practices for deploying and managing models in production.
• Experience with modern data platforms like Microsoft Fabric for data modeling and integration.
• Experience working with and consuming data from REST APIs.

Job responsibilities:

• Model Development & Implementation: Lead the end-to-end lifecycle of machine learning projects, from problem formulation and data exploration to designing, building, and deploying advanced statistical, NLP, and/or reinforcement learning models in production environments.
• Advanced Statistical Analysis: Apply a strong background in statistical computing to design and execute complex experiments (including A/B testing, fractional factorial design, and response surface methodology) to optimize systems and products.
• Algorithm & Solution Design: Architect and implement novel algorithms for multi-objective optimization and synthetic data generation, including stochastic process simulations, to solve unique business challenges.
• Technical Leadership & Mentorship: Provide technical guidance and mentorship to junior and mid-level data scientists, fostering their growth through code reviews, knowledge sharing, and collaborative problem-solving.
• Cross-Functional Collaboration: Work closely with product managers, engineers, and business stakeholders to identify opportunities, define project requirements, and translate complex scientific concepts into actionable business insights.
• Research & Innovation: Stay at the forefront of the machine learning and data science fields, continuously researching new techniques and technologies to drive innovation and maintain our competitive edge.