Associate Director, Analytical Engineering

Bristol Myers Squibb • Princeton, NJ

4d • Hybrid

About The Position

Bristol Myers Squibb is seeking an Associate Director, Analytical Engineering to contribute to the development, deployment, and maintenance of data science and machine learning pipelines, solutions, and products in support of commercialization strategies. This role involves being a member of a hands-on team of data engineers and machine learning engineers, collaborating cross-functionally with analytics and business stakeholders to pilot and deploy advanced data science solutions. The position requires designing, implementing, and maintaining reliable, scalable, and maintainable pipelines for data science products and machine learning applications, establishing best practices for machine learning engineering, data engineering, and machine learning operations, and developing and optimizing tools and frameworks to improve the efficiency and effectiveness of data scientists. The Associate Director will partner with leadership to monitor emerging trends in data science and engineering technologies to enhance organizational capabilities, translate models, pipelines, and technical solutions into clear terms for diverse stakeholders, and build and maintain data science-related applications using frameworks. Additionally, the role involves applying natural language processing techniques and advanced analytics methods to address complex business problems and contribute to the continuous evolution of the organization’s business intelligence and analytics capabilities. Telecommuting is permitted up to 3 days per week.

Requirements

• Bachelor’s degree or foreign equivalent in Data Science, Statistics, Business Analytics, Project Management, or a related field, and five (5) years of progressive postbaccalaureate related work experience as a Data Scientist or related occupation.
• Alternatively, a master’s degree or foreign equivalent in Data Science, Statistics, Business Analytics, Project Management, or a related field, and three (3) of related work experience.
• Three (3) years of experience in working in a cloud-based environment including Amazon Web Services, Azure, or Google Cloud Platform.
• Three (3) years of experience in designing and deploying Regression models and Classification models using Scikit-Learn, TensorFlow, or PyTorch.
• Three (3) years of experience in programming and version control using Python, R, SQL, and GIT.
• Three (3) years of experience in translating raw data into visuals using Tableau.
• Three (3) years of experience in automating MLOps including ML pipelines using MLflow.
• Three (3) years of experience in building and deploying data science applications in Dash or Streamlit.

Responsibilities

• Contribute to the development, deployment, and maintenance of data science and machine learning pipelines, solutions, and products in support of commercialization strategies.
• Serve as a member of a hands-on team of data engineers and machine learning engineers.
• Collaborate cross-functionally with analytics and business stakeholders to pilot and deploy advanced data science solutions.
• Design, implement, and maintain reliable, scalable, and maintainable pipelines for data science products and machine learning applications.
• Establish best practices for machine learning engineering, data engineering, and machine learning operations.
• Develop and optimize tools and frameworks that improve the efficiency and effectiveness of data scientists.
• Partner with leadership to monitor emerging trends in data science and engineering technologies to enhance organizational capabilities.
• Translate models, pipelines, and technical solutions into clear terms for diverse stakeholders.
• Build and maintain data science-related applications using frameworks.
• Apply natural language processing techniques and advanced analytics methods to address complex business problems and contribute to the continuous evolution of the organization’s business intelligence and analytics capabilities.

Benefits

• Annual discretionary bonus
• Healthcare: Medical, pharmacy, dental, and vision care.
• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Work-life benefits: Flexible time off (unlimited, with manager approval), 11 paid national holidays (with exceptions), 160 hours annual paid vacation for new hires (with manager approval), 3 optional holidays, unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs, and an annual Global Shutdown between Christmas and New Years Day.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager