Associate Director, Analytics Engineering

Key Skills

AWS, Azure, CDASH, Dash framework, Data science techniques, Machine learning techniques, Microsoft Office suites, Microsoft-Excel, MLOps tools, Natural Language Processing (NLP), Python Programming, PyTorch, R Programming, R-Shiny, Scikit-learn, SQL, Tableau, TensorFlow

Job Description

In support of Commercialization Strategy, the Associate Director of Analytics Engineering team provides technical expertise to develop, deploy, and maintain data science and machine learning related pipelines, solutions, and products.

Key Responsibilities and Major Duties

• Member of a hands-on team of data engineers and machine learning engineers.
• Work cross functionally with analytics and business stakeholders to rapidly pilot and deploy a wide variety of data science and machine learning solutions.
• Hands-on design, deployment, and maintenance of pipelines for data science related products and machine learning solutions, ensuring reliability, scalability, and maintainability.
• Develop a close working relationship with data science teams to facilitate and implement best practices relating to machine learning engineering, data engineering, and MLOps.
• Lead the development and maintenance of cutting-edge tools and frameworks empowering data scientists to work efficiently and effectively.
• Partner with the Director of Analytics engineering to monitor the rapidly evolving data science and engineering landscape providing strategic view on novel capabilities that enhance the efficiency and effectiveness of our team in support of continuous BIA evolution and business performance.
• Be able to translate the complexity of the pipelines, models and solutions at an appropriate level needed for a wide variety of stakeholders.
• Build, deploy, and maintain data science related applications made in frameworks like Dash, Streamlit and R Shiny.
• Apply NLP techniques and understand how they can be leveraged to solve business problems.

Qualifications/Degree/Certification/Licensure

• BA/BS required (quantitative area of study preferred).
• MBA/other graduate degree preferred.
• Minimum of 5 years of experience and relevant advanced degrees contribute to required years of experienc preferred
• Proficiency in Python/R, SQL, Tableau and MS Office Suite.
• Hands on experience with designing and deploying machine learning models using Scikit-Learn, TensorFlow, PyTorch, etc. is preferred.
• Experience with Git.
• Experience with cloud-based environments (AWS, Azure, etc.).
• Experience with MLOps.
• Proven experience in leading large, complex projects with multi-function team members.
• Excellent communications and presentation skills. Proven ability to explain complex analyses and outcomes to both technical and non-technical stakeholders.

The starting compensation for this job in Washington state is a range from $149,000 - $188,000, plus incentive cash and stock opportunities (based on eligibility). The starting pay rate takes into account characteristics of the job, such as required skills and where the job is performed. Final, individual compensation will be decided based on demonstrated experience. 

Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit our BMS Career Site. 

Benefit offerings are subject to the terms and conditions of the applicable plans then in effect and may include the following: Medical, pharmacy, dental and vision care. Wellbeing support such as the BMS Living Life Better program and employee assistance programs (EAP). Financial well-being resources and a 401(K). Financial protection benefits such as short- and long-term disability, life insurance, supplemental health insurance, business travel protection and survivor support. Work-life programs include paid national holidays and optional holidays, Global Shutdown days between Christmas and New Year’s holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. Parental, caregiver, bereavement, and military leave. Family care services such as adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, and child, elder and pet care resources. Other perks like tuition reimbursement and a recognition program.