Senior Data Scientist- Pharmaceuticals

We are looking for a motivated and self-driven full stack data scientist to join our expanding Data Science Services (DSS) team in North America. Zifo serves the pharmaceutical, biotech, and health industries by accelerating the discovery, development, and manufacturing of new drugs, therapies, and vaccines—to save lives faster! 

As part of the DSS team, you will work with global teams comprised of engineers, scientists, architects, and consultants to drive data readiness & data science initiatives for the Life Sciences industry. You are expected to continuously learn & be the expert to support broader enterprise vision, Go-to-Market (GTM) & growth strategies, and author whitepapers.

Requirements

Responsibilities:

• Master data management frameworks, engineering standards & data science use-cases,
• Architect complex data products, data science solutions & enterprise deployments,
• Support or lead business growth initiatives from executing POCs, to leading GTM efforts,
• Support or lead technical & commercial discussions with clients and partners,
• Support or lead global services & solutions delivery team

Required Experience:

• Demonstrable experience in project & stakeholder management,
• Strong conceptualization, presentation & storytelling skills,
• Familiarity with data management, governance frameworks & best practices,
• Experience building mature data products or Data-As-A-Service solutions,
• Strong software engineering skills (code reusability, version control, integration tests), etc.
• Expert in any two programming languages - Python, Spark, Scala, SQL and R,
• Experience in any one of the following - health sciences, clinical operations, or life sciences

Good To Have:

• Experience with at-least one cloud provider (AWS, Azure), storage & data management platforms
• Experience working with EHR, claims, disease registries & patient generated health data
• Familiarity with data observability, lineage, semantic data layer, & related concepts
• Experience with data science libraries such as PyTorch, TensorFlow, HuggingFace, etc. 
• Experience in NLP, NLU, large generative models, LangChain, etc.
• Understanding of AIML lifecycle, MLOps, explainable & responsible AI

Qualifications:

• Master’s or PhD degree in Data Sciences /Life Sciences/ Bioinformatics / Computer Science or related field
• At-least six years of experience after Masters education or four years after PhD.

A successful “Zifo” member is:

• Independent, self-motivated & results driven,
• Humble, empathetic, with emotional & cultural intelligence
• Quickly & continually acquires new skills & business principles,
• Curious and always looking for creative solutions to complex problems.

Benefits

CURIOSITY DRIVEN, SCIENCE FOCUSED, EMPLOYEE BUILT. Our culture is unlike any other, one where we debate, challenge ourselves, and interact with all alike. We are a curious bunch, characterized by our passion to learn and spirit of teamwork. Zifo is a global R&D solutions provider focused on the industries of Pharma, Biotech, Manufacturing QC, Medical Devices, specialty chemicals and other research-based organizations. Our team’s knowledge of science and expertise in technology help Zifo better serve our customers around the globe, including 7 of the Top 10 Biopharma companies.

We look for Science – Biotechnology, Pharmaceutical Technology, Biomedical Engineering, Microbiology etc. We possess scientific and technical knowledge and bear professional and personal goals. While we have a “no doors” policy to promote free access within, we do have a tough door to walk in. We search with a two-point agenda – technical competency and cultural adaptability.

We offer a competitive compensation package including accrued vacation, medical, dental, vision, 401k with company matching, life insurance, and flexible spending accounts.

If you share these sentiments and are prepared for the atypical, then Zifo is your calling!

Zifo is an equal opportunity employer, and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.