Biotech Health Data Governance Lead

Alignerr
Oxford
2 weeks ago
Applications closed

Related Jobs

View all jobs

Biotech Health Data Governance Lead

Biotech Health Data Governance Lead

Biotech Health Data Governance Lead

Biotech Health Data Governance Lead

Biotech Health Data Governance Lead

Remote Biotech Health Data Governance Lead

About The Job

At Alignerr, we partner with the world’s leading AI research teams and life sciences organizations to build and train cutting‑edge AI models using high-quality, trustworthy data. We are seeking a Biotech Health Data Governance Lead to ensure that research and clinical trial data is accurate, traceable, compliant, and ready to support scientific discovery, regulatory filings, and advanced analytics.


Organization

Organization: Alignerr
Position: Biotech Health Data Governance Lead
Type: Hourly Contract
Compensation: $40–$80 /hour
Location: Remote
Commitment: 10–40 hours/week


What You’ll Do

  • Govern biotech research and clinical trial data to ensure accuracy, lineage, and auditability for scientific analysis and regulatory submissions.
  • Define and enforce data policies for classification, access, security, and metadata across research, clinical, regulatory, and partner teams.
  • Enable secure, governed access to data for analytics, innovation, and external collaborations while protecting confidential and patient‑related information.

What We’re Looking For

  • Experience leading or implementing data governance programs in biotech, life sciences, clinical research, or regulated data environments.
  • Strong understanding of data privacy, security, compliance, and regulatory expectations for research and clinical trial data.
  • Ability to collaborate across scientific, IT, compliance, and business teams to align data standards and workflows.

Preferred

  • Prior experience with data annotation, data quality, or evaluation systems

Why Join Us

  • Competitive pay and flexible remote work.
  • Lead data governance initiatives that support cutting‑edge AI and life sciences research.
  • Exposure to advanced AI models and how high‑quality data enables better science.
  • Freelance perks: autonomy, flexibility, and global collaboration.
  • Potential for contract extension.

Application Process (Takes 15‑20 min)

  • Submit your resume
  • Complete a short screening
  • Project matching and onboarding

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.