Lead Data Scientist

Mastech Digital; United States; Remote; USD 100,000 - 720,000; Full time

Job summary

A leading company is seeking a Lead Data Scientist to manage projects and teams in the pharma sector. This remote role requires expertise in data science, leadership abilities, and a background in life sciences. Ideal candidates are expected to communicate findings effectively and implement strategic data initiatives to advance business objectives.

Qualifications

• Experience in pharma-specific data science roles.
• Background in life sciences, medicine, or pharma preferred.
• Mid-Senior level position.

Responsibilities

• Manage and mentor data science teams.
• Develop data strategies aligned with business goals.
• Plan and oversee data science projects.

Skills

Leadership

Data Analysis

Project Management

Communication

Technical Expertise

Job description

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W2 Only. Fully remote. Need prior Pharma experience

Title: Lead Data Scientist

Location: Fully Remote

Duration: 12+ Months

working in pharma-specific data science roles, having a background in life sciences, medicine, or pharma can be very helpful. It allows you to better understand the data (like clinical trials, genomics, or drug development pipelines) and communicate effectively with subject matter experts.

Responsibilities of a Data Science Technical Lead:

• Team Leadership: Manage and mentor data science teams, providing guidance and support.
• Technical Expertise: Stay current with the latest advancements in data science, machine learning, and related technologies.
• Strategic Planning: Develop data strategies aligned with business goals and objectives.
• Project Management: Plan, prioritize, and oversee data science projects, ensuring timely delivery and successful outcomes.
• Collaboration: Work with cross-functional teams, including engineering, product management, and business stakeholders.
• Problem Definition and Solution: Define complex business problems and translate them into data science solutions.
• Data Analysis and Modeling: Conduct data exploration, analysis, and modeling to extract meaningful insights.
• Communication and Presentation: Communicate findings and recommendations effectively to both technical and non-technical audiences.
• Ethical Considerations: Ensure data science projects are ethically sound and compliant with relevant regulations.
• Continuous Improvement: Identify and implement process improvements to enhance team efficiency and productivity.

Regards,

Yogesh Singh Rana

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting and Software Development

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