At a Glance
- Tasks: Deliver impactful data science projects and translate insights into actionable strategies.
- Company: Join a leading analytics team in a dynamic and innovative environment.
- Benefits: Competitive salary, professional development, and opportunities for client engagement.
- Other info: Fast-paced role with excellent career growth and collaboration across teams.
- Why this job: Make a real difference by optimising client operations with your data expertise.
- Qualifications: 2+ years in data science, strong skills in Python, R, and SQL.
The predicted salary is between 40000 - 50000 £ per year.
As a Data Scientist within the Analytics Team, you will contribute to data-driven strategies for our clients. You will work closely with the Data & Analytics Manager and senior colleagues, deliver data science projects, and collaborate with stakeholders across data strategy, sales, account management, delivery and marketing. You are expected to bring solid technical skills and commercial awareness to deliver data solutions that drive measurable operational performance. This is a hands‑on role ideal for someone who thrives on translating data into actionable insight and producing high‑quality outcomes.
Responsibilities
- Deliver data science projects, from problem definition through to actionable insights and presentation of results.
- Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes.
- Build and maintain data pipelines, ensuring data quality, consistency, and integrity across multiple sources and formats.
- Translate complex analyses into clear, commercially relevant recommendations for clients and internal stakeholders.
- Work with client teams to identify analytical opportunities, support marketing strategy, and quantify the impact of data-driven decision-making.
- Support pre-sales and client engagement, helping to demonstrate the value of data insight.
- Follow best practices in data science, reproducible research, and ethical AI.
- Collaborate cross-functionally to enhance the company's products and marketing data solutions.
What Success Looks Like in the Role
- Delivery of impactful, high-quality analytics that directly inform and improve client marketing outcomes.
- Building trust and credibility with clients as an analytical consultant.
- Regular iteration on machine learning methodologies, tools, and frameworks.
- Consistent demonstration of technical excellence and commercial insight in all project deliverables.
- Measurable contribution to the enhancement of Sagacity's data science and analytics product suite.
Competencies and Experience
- 2+ years’ experience in data science, analytics, or statistical modelling, ideally with commercial experience within the Telecoms, Banking or Utilities industries or within a data-related consultancy.
- Educated to degree level (postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar.
- Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP).
- Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering.
- Strong command of SQL and familiarity with data engineering environments such as Databricks or similar.
- Skilled in data visualisation and storytelling using tools such as Power BI, Tableau, Plotly, or Sigma.
- Demonstrated ability to translate technical findings into strategic recommendations for non-technical audiences.
- Commercially aware, with proven success in applying analytics to solve business problems.
- Strong communicator; able to engage stakeholders and present findings with clarity and confidence.
- Self‑motivated, organised, and proactive, with the ability to manage multiple priorities and stakeholders in a fast‑paced environment.
- Willing to travel across the UK for client engagements.
- Must have the right to work in the UK and a commitment to ongoing professional development.
Data Scientist in London employer: Occupop
As a Data Scientist at our company, you will be part of a dynamic Analytics Team that values innovation and collaboration. We offer a supportive work culture that encourages professional growth through hands-on projects and cross-functional teamwork, all while making a tangible impact on client outcomes. Located in the heart of the UK, we provide a stimulating environment where your technical skills can flourish, and your contributions are recognised and rewarded.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, predictive models, and any cool visualisations you've made. This is your chance to demonstrate how you turn data into actionable insights.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your past projects. Practice explaining complex analyses in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight how your experience aligns with our mission and values.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your technical skills and experience in data science. We want to see how you've used predictive modelling and machine learning techniques in real-world scenarios, so don’t hold back!
Tailor Your Application:Take a moment to customise your application for the Data Scientist role. Mention specific projects or experiences that align with our needs, especially those that demonstrate your ability to deliver actionable insights.
Be Clear and Concise:When writing your application, clarity is key! Use straightforward language to explain complex analyses and ensure your recommendations are easy to understand. Remember, we value communication just as much as technical prowess.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Occupop
✨Know Your Data Science Stuff
Make sure you brush up on your technical skills, especially in Python, R, and SQL. Be ready to discuss specific projects where you've applied machine learning techniques or built data pipelines. This will show that you can deliver high-quality analytics and understand the technical side of things.
✨Translate Data into Insights
Prepare examples of how you've turned complex analyses into clear, actionable insights for clients or stakeholders. Practice explaining your findings in a way that's easy to understand, as this role requires strong communication skills to engage non-technical audiences.
✨Show Your Commercial Awareness
Familiarise yourself with the industry trends in Telecoms, Banking, or Utilities. Think about how data science can solve real business problems in these sectors. Being able to discuss the commercial impact of your work will impress the interviewers and demonstrate your understanding of the role.
✨Be Ready for Collaboration
Since this role involves working closely with various teams, be prepared to talk about your experience collaborating cross-functionally. Share examples of how you've worked with marketing or sales teams to identify analytical opportunities and support their strategies.
