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How to Get a Better Data Science Job After a Lay-Off or Redundancy
Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand.
Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation.
This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.
Contents
Understanding Redundancy in Data Science
Step 1: Reset and Reflect
Step 2: Define Your Strengths and Specialisms
Step 3: Update Your CV and Data Science Portfolio
Step 4: Optimise LinkedIn and Kaggle/GitHub Profiles
Step 5: Reach Out to Recruiters and Hiring Managers
Step 6: Apply Strategically and Follow Up
Step 7: Upskill and Deepen Your Knowledge
Step 8: Consider Contract, Research or Remote Roles
Step 9: Look After Your Finances and Wellbeing
Bonus: Top UK Employers Hiring Data Scientists in 2025
Final Thoughts: Redundancy Can Be a Reset
Understanding Redundancy in Data Science
Data science teams can face redundancy due to budget cuts, changing business priorities, or shifting AI strategies. It’s not about your talent—it’s often just the numbers.
The UK still has strong demand for skilled data scientists who can:
Deliver insights using Python, SQL, R
Build predictive models (classification, regression, clustering)
Use cloud tools (AWS, GCP, Azure)
Communicate results effectively to stakeholders
Step 1: Reset and Reflect
Use your redundancy as a moment to re-centre:
Reflect on past successes and challenges
Clarify what kind of work and culture you want
Consider which sectors interest you most (e.g. health, climate, fintech, edtech)
This clarity helps you avoid jumping into just anything.
Step 2: Define Your Strengths and Specialisms
Pinpoint your technical and domain strengths:
Are you strongest in modelling, analytics, NLP, computer vision, or experimentation?
Do you prefer building end-to-end solutions or deep-diving into model development?
What tools and platforms do you know? (e.g. Pandas, Scikit-learn, TensorFlow, PyTorch, SQL, Power BI, dbt)
Step 3: Update Your CV and Data Science Portfolio
Your CV should include:
A summary that reflects your direction and value
Key achievements with measurable impact (e.g. “Reduced churn by 18% using a random forest model”)
Tools, frameworks, and data sources used
A link to your portfolio site, GitHub, or Kaggle profile
Keep it targeted and highlight transferable skills.
Step 4: Optimise LinkedIn and Kaggle/GitHub Profiles
LinkedIn Tips:
Headline: “Data Scientist | Python, SQL, ML | Open to Work”
About section: Summarise experience, focus areas, values
Add featured projects, visualisations, or talks
GitHub/Kaggle Tips:
Organise repos with clear READMEs and Jupyter notebooks
Include problem statements, EDA, model results, and business interpretation
Document any competitions or case studies
Sample LinkedIn About Section:
Data Scientist | Machine Learning | Open to Work
Experienced data scientist with 4+ years in predictive modelling, analytics, and stakeholder communication. Recently made redundant due to business restructuring, I’m now looking for a role where I can drive data-driven decisions and improve customer outcomes.
Tech stack: Python, SQL, Scikit-learn, Tableau, GCP, Git, NumPy, dbt
Let’s connect if you’re hiring or working on data science problems with real-world impact.
Step 5: Reach Out to Recruiters and Hiring Managers
Many data roles are filled through networks before job boards. Be proactive.
Recruiter Message Example:
Subject: Data Scientist | Available Immediately | ML & Analytics
Hi [Recruiter’s Name],
I’m exploring new data science opportunities after a recent redundancy. I bring experience in predictive modelling, SQL analysis, and stakeholder engagement. I’ve attached my CV and GitHub link, and would love to hear about any relevant openings.
Best regards,
[Your Name]
[LinkedIn]
[GitHub]
[CV attachment]
Hiring Manager Follow-Up Example:
Subject: Application – Data Scientist Role at [Company Name]
Dear [Hiring Manager],
I recently applied for the Data Scientist role and wanted to express my strong interest. I have hands-on experience building models that drive measurable impact, and I’m currently available following a redundancy.
Please find my CV attached. I’d welcome the opportunity to speak further.
Kind regards,
[Your Name]
Step 6: Apply Strategically and Follow Up
Focus on roles where you match 70%+ of the criteria
Customise your CV for each application
Use data keywords from job ads (important for ATS)
Keep a tracker of jobs, contacts, and application stages
Follow up if you’ve had no response after 10 days.
Step 7: Upskill and Deepen Your Knowledge
Use your time to grow your capabilities:
Take courses on platforms like Coursera, DataCamp, Udacity, or fast.ai
Contribute to open-source or build a case study project
Learn tools like dbt, Airflow, Power BI, Looker
Join virtual meetups or data science Slack groups
Step 8: Consider Contract, Research or Remote Roles
Short-term and flexible work can bridge the gap:
Look for freelance or contract roles on platforms like Turing, Toptal, or Upwork
Explore research assistant roles at universities or think tanks
Check remote-friendly positions via www.datascience-jobs.co.uk
Step 9: Look After Your Finances and Wellbeing
Redundancy is stressful. Don’t overlook your personal care:
Apply for any redundancy pay, Universal Credit, or JSA
Use MoneyHelper or StepChange for financial guidance
Build a daily routine for job search, skill-building, rest
Stay connected to others in the industry to avoid isolation
Bonus: Top UK Employers Hiring Data Scientists in 2025
NHS England (Data & Analytics)
Deliveroo
The Alan Turing Institute
Monzo Bank
Meta (London AI & Data Science)
ASOS
Babylon Health
Spotify (UK Data Team)
Boots
GSK
YouGov
Starling Bank
Ocado Technology
BT Group
Government Digital Service (GDS)
Browse live roles at www.datascience-jobs.co.uk
Final Thoughts: Redundancy Can Be a Reset
Redundancy is not the end of your career—it could be the beginning of your most purposeful work yet.
With the right strategy, mindset, and visibility, you can land a role that plays to your strengths and future goals.
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Visit: www.datascience-jobs.co.uk
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