Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to enhance recommendation systems using AI and machine learning.
- Company: Be part of a forward-thinking company focused on user experience and equitable relationships.
- Benefits: Enjoy a 12-month contract with flexible working options and opportunities for professional growth.
- Why this job: Make a real impact by driving product innovation and collaborating with top talent in the field.
- Qualifications: Degree in a quantitative field and experience with recommendation engines and statistical modelling required.
- Other info: This role is outside IR35, offering you more flexibility in your contract.
The predicted salary is between 48000 - 72000 £ per year.
We are seeking a Senior Data Scientist to join a cross-functional Recommendations group, a team of dedicated engineers, scientists, and machine learning specialists focused on developing and improving advanced recommendation systems across a portfolio of widely used applications. Collaborating with product teams and other engineering groups, the team leverages AI and machine learning to enhance user experiences and drive the mission of fostering healthy, equitable relationships.
Key Responsibilities
- Collaborate with machine learning scientists and engineers in a cross functional team environment.
- Identify high-value opportunities and design frameworks to evaluate algorithmic improvements.
- Conduct large-scale experiments to validate hypotheses and guide product innovation.
- Analyse the impact of algorithm changes on marketplace dynamics and user engagement.
- Partner with business and technical stakeholders to translate complex problems into scalable AI solutions.
- Work closely with Product Management to define roadmaps and establish key metrics aligned with strategic goals.
Previous experience
- A degree in Computer Science, Mathematics, or a related quantitative field (e.g., economics, social science).
- Experience working with recommendations engines within data science.
- Strong statistical modelling expertise, including hypothesis testing, inference, and regression analysis.
- Proficiency in Python data science libraries (e.g., pandas, scikit-learn, numpy, statsmodels).
- Advanced SQL skills, including experience with analytic functions, performance optimization, and data manipulation.
- Familiarity with multi-sided marketplaces or the online relationship space.
- Experience applying advanced statistical methods in academic or industry settings.
- Understanding of the machine learning development lifecycle, including MLOps and CI/CD.
- Hands-on experience deploying and maintaining machine learning models.
Senior Data Scientist employer: TechNET IT Recruitment Ltd
Contact Detail:
TechNET IT Recruitment Ltd 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 recommendation systems and AI technologies. This will not only help you during interviews but also demonstrate your passion for the field and your commitment to staying updated.
✨Tip Number 2
Network with professionals in the data science community, especially those who have experience in recommendation engines. Attend meetups or webinars to gain insights and potentially get referrals that could boost your application.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented machine learning solutions. Be ready to explain your thought process, the challenges you faced, and how you measured the impact of your work.
✨Tip Number 4
Showcase your collaboration skills by highlighting experiences where you've worked in cross-functional teams. Emphasise your ability to communicate complex ideas clearly to both technical and non-technical stakeholders.
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 recommendation engines. Emphasise your statistical modelling expertise and proficiency in Python and SQL, as these are key requirements for the role.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about working in a cross-functional team and how your previous experiences align with the responsibilities outlined in the job description. Mention specific projects where you've successfully applied machine learning techniques.
Showcase Relevant Projects: If you have worked on projects involving algorithmic improvements or large-scale experiments, be sure to include these in your application. Detail your role, the challenges faced, and the outcomes achieved to demonstrate your impact.
Highlight Collaboration Skills: Since the role involves partnering with various stakeholders, emphasise your ability to collaborate effectively. Provide examples of how you've worked with product teams or technical stakeholders to translate complex problems into actionable solutions.
How to prepare for a job interview at TechNET IT Recruitment Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python data science libraries and SQL. Bring examples of past projects where you successfully implemented recommendation systems or conducted large-scale experiments, as this will demonstrate your technical expertise.
✨Understand the Business Context
Familiarise yourself with the company's mission and how their recommendation systems impact user engagement. Be ready to discuss how you can translate complex problems into scalable AI solutions that align with their strategic goals.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your ability to identify high-value opportunities and design frameworks for algorithmic improvements. Practice articulating your thought process in tackling these challenges, as it will showcase your analytical skills.
✨Demonstrate Collaboration Skills
Since the role involves working closely with cross-functional teams, be prepared to share examples of how you've successfully collaborated with machine learning scientists, engineers, and product managers in the past. Highlight your communication skills and ability to work in a team environment.
