Lead Data Scientist - Commercial

The businesses of Merck KGaA, Darmstadt, Germany; Toronto; On-site; CAD 174,000 - 264,000; Full time

Job summary

A global healthcare company is seeking a Lead Data Scientist to shape commercial and medical strategies through advanced analytics and machine learning. This role involves collaborating across teams, leading the development of scalable AI/ML solutions, and mentoring junior data scientists. Ideal candidates should hold a Master’s degree and have a strong background in data science within a commercial setting, especially in pharma. The position offers a competitive salary and comprehensive benefits in Toronto, Ontario.

Benefits

Health insurance

Paid time off

Retirement contributions

Qualifications

• 4+ years of experience as a data scientist in a commercial setting, preferably pharma.
• Strong expertise in supervised/unsupervised learning and causal inference.
• Experience deploying Python-based machine learning models in production.

Responsibilities

• Collaborate with Commercial, Medical, and IT teams.
• Design and validate supervised and unsupervised models.
• Apply causal inference to optimize strategy and resource allocation.

Skills

Proficiency in Python (pandas, scikit-learn)

SQL

Strong communication skills

Causal inference expertise

Mentoring junior data scientists

Scalable ML pipelines

Collaboration across teams

Education

Master’s degree in a related quantitative field

Tools

Git

Linux

AWS

Job description

Work Location: Boston, Massachusetts
Shift:
Department: HC-NA-HAD2 Data Innovation 1
Recruiter: Rena Ann Peterson

This information is for internals only. Please do not share outside of the organization.

Your Role

At EMD Serono, data drives everything we do to bring innovative medicines to patients faster. As a Lead Data Scientist, you will shape commercial and medical strategies by analyzing complex datasets and applying advanced analytics and machine learning to generate actionable insights that optimize decisions, uncover opportunities, and improve patient outcomes.

Key Responsibilities

• Collaborate Across Teams: Partner with Commercial, Medical, and IT teams to identify high-impact problems and deliver analytics solutions aligned with business goals.
• Lead Advanced Analytics: Design, validate, and interpret supervised (regression, classification) and unsupervised models (clustering, dimensionality reduction) to drive decision-making and identify new opportunities.
• Causal Inference Expertise: Apply causal inference to experimental and observational data to optimize strategy and resource allocation.
• Scalable AI/ML Solutions: Build scalable AI/ML pipelines for large, high-dimensional datasets.
• Mentorship and Leadership: Mentor junior data scientists and foster a culture of excellence.
• Healthcare Expertise: Leverage deep knowledge of US healthcare and pharma commercial landscapes, including claims, EMR data, to deliver impactful solutions.
• Communication and Influence: Translate complex analytical findings into clear, actionable business recommendations for diverse stakeholders.

Minimum Qualifications

• Master’s degree in Statistics, Data Science, Mathematics, Physics, Econometrics, Operations Research, a related quantitative field, or equivalent work experience.
• 4+ years of experience as a data scientist in a commercial setting (pharma preferred).
• Strong expertise in supervised/unsupervised learning, causal inference, hypothesis testing, scalable ML pipelines, and feature engineering.
• Proficiency in Python (pandas, scikit-learn), SQL, Git, Linux, AWS; experience with large healthcare datasets (claims data a plus) and parquet files.

• Experience deploying Python-based machine learning models in production using containers and/or shell scripting.

• Solid business acumen and ability to prioritize high-impact problems aligned with strategic objectives.
• Strong communication skills with the ability to translate analytical findings into actionable recommendations.
• Proven ability to collaborate effectively across Commercial, Medical, and IT teams.
• Experienced in mentoring and guiding junior data scientists in advanced techniques and best practices.

Preferred Qualifications

• 6 or more years of work experience as a data scientist in a commercial setting (pharma preferred) with a Master’s degree, or
• 4+ years with a PhD degree.
• Prior experience with marketing mix models (especially in pharma).
• US healthcare and pharma commercial expertise strongly preferred.
• Demonstrated ability to leverage genAI tools and techniques for extracting features from text in a commercial context.

Location

On-site Seaport MA

Pay range for this position: $126,800 - 191,700. The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job‑related factors. Position may be eligible for sales or performance‑based bonuses. Benefits offered by the Company include health insurance, paid time off (PTO), retirement contributions, and other perquisites. For more information click here.

The Company is an Equal Employment Opportunity employer. No employee or applicant for employment will be discriminated against on the basis of race, color, religion, age, sex, sexual orientation, national origin, ancestry, disability, military or veteran status, genetic information, gender identity, transgender status, marital status, or any other classification protected by applicable federal, state, or local law. This policy of Equal Employment Opportunity applies to all policies and programs relating to recruitment and hiring, promotion, compensation, benefits, discipline, termination, and all other terms and conditions of employment. Any applicant or employee who believes they have been discriminated against by the Company or anyone acting on behalf of the Company must report any concerns to their Human Resources Business Partner, Legal, or Compliance immediately. The Company will not retaliate against any individual because they made a good faith report of discrimination.