About this role
The team is seeking a Data Scientist with a strong background in Pharma, Life Sciences, or Biotech datasets. This role requires a professional who can immediately contribute to commercial measurement and causal analytics. The ideal candidate will possess a deep understanding of experimental design, statistical measurement, and observational causal inference, moving beyond standard machine learning modeling.
Key Responsibilities:
- Develop and implement causal analytics frameworks to measure impact and lift.
- Design experiments and observational studies to derive actionable insights.
- Analyze complex datasets to identify trends and patterns relevant to commercial objectives.
- Collaborate with cross-functional teams to integrate findings into business strategies.
- Communicate complex statistical concepts to non-technical stakeholders.
Required Skills & Qualifications:
- Proven experience in causal analytics, lift measurement, and impact attribution.
- Strong knowledge of experimental design and statistical methods.
- Proficiency in data analysis tools and programming languages (e.g., Python, R).
- Experience with Pharma, Life Sciences, or Biotech datasets is mandatory.
- Excellent problem-solving skills and attention to detail.
Experience:
- Minimum of 5-8 years in data science or a related field, with a focus on causal analytics.
What we offer:
- Opportunity to work in a dynamic and innovative environment.
- Collaboration with industry experts and thought leaders.
- Professional development and growth opportunities.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.