At a Glance
- Tasks: Lead data science projects and mentor junior team members while delivering impactful insights.
- Company: Join a thriving consultancy working with top consumer brands in the UK and globally.
- Benefits: Enjoy a competitive salary, hybrid work model, and opportunities for project ownership.
- Why this job: Be part of a growing team that values innovation and collaboration in data science.
- Qualifications: Proficiency in Python/PySpark is essential; consulting experience is a plus.
- Other info: This role offers a chance to shape solutions for major brands and enhance your career.
The predicted salary is between 45000 - 75000 ÂŁ per year.
Direct message the job poster from Harnham
I’m working with a mission-driven healthcare technology company that leverages real-world data to improve health outcomes and equity. They focus on understanding the complex social and behavioral factors that influence healthcare decisions, going beyond traditional clinical data. The company has evolved from a nonprofit origin into a fast-growing, globally distributed tech organization.
They generate revenue through consulting with pharmaceutical clients and by offering innovative data products aimed at transforming healthcare strategies.
The Role
As a Senior Data Scientist, you will be a key technical leader on their core data products. Your primary focus will be building and deploying predictive machine learning models using large-scale, complex datasets — including consumer data, survey data, and extensive geospatial information.
You will take ownership not only of modeling and metric development but also of the end-to-end ML lifecycle, including deployment and monitoring using modern MLOps frameworks. Collaboration with data engineers and cross-functional teams is essential, as you’ll help shape the ML strategy and drive innovation in how healthcare behaviors are understood and acted upon.
What You’ll Bring
- PhD in a quantitative or scientific field, with proven commercial experience as a Data Scientist or ML Engineer
- Exposure to behavioral or consumer data is essential, preferably in the Healthcare space
- Strong Python skills and experience with Databricks or similar platforms
- Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar)
- Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying models in cloud environments (GCP, AWS, or Azure)
- Proactive, creative problem solver with a startup mindset and strong communication skills
- Comfortable taking technical ownership and leading ML projects from end to end
If you are interested, please share your CV with rosie@harnham.com
Seniority level
- Seniority levelMid-Senior level
Employment type
- Employment typeFull-time
Job function
- Job functionAnalyst, Engineering, and Consulting
- IndustriesPublic Health and Retail Pharmacies
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Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in data science, especially in areas like clustering and propensity modelling. This will not only help you during interviews but also show your genuine interest in the field.
✨Tip Number 2
Network with professionals in the data science community, particularly those who work in consultancy or retail. Engaging in conversations can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects in detail, especially those involving Python and PySpark. Be ready to explain your thought process and the impact of your work on business outcomes.
✨Tip Number 4
Showcase your mentoring experience, if applicable. Highlighting how you've guided other data scientists can demonstrate your leadership skills, which are crucial for a senior role.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with Python and PySpark. Emphasise any consulting or retail experience you have, as well as your ability to mentor others.
Craft a Compelling Cover Letter: Write a cover letter that showcases your understanding of the role and the company. Mention specific projects you've led or contributed to, especially those involving clustering, propensity modelling, or NLP.
Showcase Your Skills: In your application, clearly outline your technical skills and how they relate to the job description. Provide examples of how you've used these skills to solve business problems or deliver insights.
Follow Application Instructions: Ensure you send your application to Theo via the apply link provided. Double-check that all documents are attached and that your contact information is correct before hitting send.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Make sure to highlight your experience with Python and PySpark during the interview. Be prepared to discuss specific projects where you've used these tools to create propensity models or clustering solutions.
✨Demonstrate Commercial Awareness
Since the role requires commercial insights, think of examples where your data science work has directly impacted business decisions. Be ready to explain how your analyses have added value to previous projects.
✨Prepare for Client Interaction Scenarios
As this position involves leading client relationships, practice discussing how you would approach scoping out business problems and delivering insights. Consider role-playing these scenarios with a friend to build confidence.
✨Emphasise Mentorship Experience
If you have experience mentoring other data scientists, be sure to mention it. Discuss how you've supported team members in their projects and the impact it had on their development and the team's success.