At a Glance
- Tasks: Lead data science projects, ensuring high-quality machine learning solutions are delivered.
- Company: Join a forward-thinking organisation focused on innovation and technical excellence.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and elevate the technical standards across the organisation.
- Why this job: Make a real impact by shaping the future of data science in a dynamic environment.
- Qualifications: Extensive experience in data science, strong leadership skills, and expertise in cloud platforms.
The predicted salary is between 63000 - 77000 £ per year.
This role exists to provide technical leadership and assurance across data science, ensuring machine learning solutions are designed, built, and operated to a high and consistent technical standard.
The role focuses on enabling scalable, reliable delivery of data science solutions aligned to business priorities defined elsewhere.
WHAT YOU'LL BE DOING
- Acting as a technical lead for data science , guiding modelling approach and solution design across multiple initiatives.
- Working closely with business stakeholders to translate priority use cases into technically sound, production‑ready data science solutions .
- Providing hands‑on technical leadership across the data science lifecycle, from problem framing and modelling through deployment and ongoing optimisation.
- Defining and embedding technical standards and best practices for experimentation, validation, documentation, and reproducibility.
- Reviewing and challenging technical designs and implementations, providing clear technical direction and sign‑off .
- Supporting and mentoring data scientists on complex technical challenges.
- Partnering with Data Architecture, ML & Data Engineering, and BI teams to ensure solutions are scalable, robust, and production‑ready.
- Evaluating new techniques and tools, guiding their pragmatic adoption.
- Communicating technical assumptions, risks, and trade‑offs clearly to technical and non‑technical stakeholders.
Accountable for
- The technical quality and consistency of data science solutions delivered within assigned domains.
- Ensuring solutions meet agreed performance, scalability, reliability, and maintainability standards.
- Consistent application of data science standards, reducing delivery risk and technical debt.
- Providing ongoing technical assurance that solutions remain fit for production as usage and complexity increase.
- Maintaining strong technical partnerships with stakeholders as a trusted advisor.
- Raising the overall technical maturity of data science within the organisation
WHAT YOU'LL NEED
Essential Criteria
- Extensive experience delivering production‑grade, commercially impactful data science solutions, gained in a data science or machine learning roles.
- Proven experience operating as a senior technical lead, reviewer, or technical sign‑off authority.
- Strong experience building ML solutions on cloud platforms (GCP, AWS, or Azure).
- Advanced expertise in Python and SQL.
- Deep applied knowledge of machine learning techniques, including regression, classification, clustering, and time‑series forecasting.
- Experience supporting production deployment and lifecycle management of ML models.
- Strong understanding of data warehousing, data modelling, and modern data architecture.
- Excellent communication skills, able to explain technical decisions clearly to non‑technical stakeholders.
Preferred Skills
- Experience with recommender systems or personalisation use cases.
- Familiarity with MLOps concepts and production ML practices.
- Demonstrated ability to raise technical standards through influence rather than authority.
- Experience in an e‑commerce or retail environment.
Lead Data Scientist in Solihull employer: Gymshark
Gymshark is an excellent employer that fosters a vibrant and inclusive work culture, where team members are encouraged to grow and develop their skills in the dynamic fitness retail environment. With a focus on exceptional customer service and brand representation, employees enjoy the benefits of flexible working hours, a supportive team atmosphere, and opportunities for personal and professional growth, all while being part of a leading fitness brand in the UK.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist in Solihull
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Gymshark!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Scientist at Gymshark.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Gymshark.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Scientist at Gymshark, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data Scientist in Solihull
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Gymshark, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Gymshark. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Gymshark
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Gymshark!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
