At a Glance
- Tasks: Lead data science projects and bridge the gap between engineering and strategy.
- Company: Join Ekimetrics, a forward-thinking company focused on digital transformation.
- Benefits: Enjoy competitive salary, hybrid work, and extensive leave.
- Other info: Be part of a dynamic team with excellent growth opportunities.
- Why this job: Make a real impact by driving innovative solutions for top clients.
- Qualifications: 5+ years in data science with strong technical and strategic skills.
The predicted salary is between 70000 - 90000 £ per year.
We have an exciting opportunity for a Data Science Manager to join our London team! The Data Science Manager will be a bridge between data Engineering & Architecture and the data science team. This is a key role within Ekimetrics, your focus being on digital strategy and transformation initiatives that will lead to significant, value-led transformation for our clients. You’ll be acting as a strategic partner to our clients, gaining a deep understanding of their needs and offering the most effective solutions, providing impactful and useful insights to help steer their revenue or data strategies, and building long‑term relationships. You will be responsible for bringing clients' proof of concepts to life or leading the development of new solutions. This role will require a blend of strategic thinking, business acumen, an understanding of Gen AI, and most importantly project management skills.
Accountabilities
- Be part of commercial activities, pitching to prospective clients
- Steer and manage large projects for globally recognised clients
- Manage end‑to‑end Data Science & AI projects, including planning, design, and implementation.
- Work on Data Science transformations working with Gen AI, LLMs & NLPs
- Create real valuable actionable solutions for clients.
- Manage and coach a small team of 3-10 consultants.
- Be a HR mentor responsible for the growth of junior employee’s career development.
About You
We are looking for someone who is able to wear 2 hats – the data scientist and the strategic consultant – and so you’ll need to show both advanced technical acumen and a strong interest in business strategy.
Requirements
- A degree in Computer Science / Engineering with 5+ years of back‑end development OR experience in developing advanced algorithms.
- Prior experience using Data Science & AI /Data Architecture/DWH/Data‑lakes in a business setting, preferably in a client‑facing, consulting-oriented role;
- Experience developing and deploying production‑ready Data Engineering pipelines.
- Expertise in key technologies related to Data Management, e.g. SQL, Spark, Python
- Experience with the Azure cloud platform
- Experience with Advanced Python Libraries i.e., Pandas, Pyspark
- Experience with development best practices (git, testing, coding standards, CI/CD, documentation, code refactoring…)
- A love of data and understanding of some algorithmic / analytics such as decision tree, clustering, NLP, regression, graph theory, neural networks etc.
- Expertise in some aspects of Data Management and readiness to grow in others: Data analytics architectures; Data governance processes and platforms; Data ingestion & transformation in data warehouses or data-lakes; Data visualisation.
- Experience in Private Equity (PE) or in sustainability using AI
Transversal Skills
- Excellent communication skills – especially translating complex technical findings into insights and stories for stakeholders (internal and external)
- A demonstrated ability to develop new and long‑lasting client relationships at senior levels across multiple industries and sectors
- An ability to work autonomously and be self‑motivated
- A team‑oriented and collaborative working style, both with clients and within Ekimetrics
- People management experience and demonstrated ability to develop younger talent and build a high performing team, (this doesn’t necessarily mean you have directly managed a team; this could relate to mentorship, project team management, etc.)
- Project management and delivery expertise
- A passion for joining a small team and desire to help the business grow quickly
Benefits
- Competitive salary + Bonus Scheme
- Hybrid working (2 days a week in the office)
- 25 days annual leave (+ Bank Holidays and additional days for tenure)
- Private healthcare, life insurance, critical illness cover, and professional wellbeing support services
- Group pension scheme
- An emphasis on work‑life‑balance and a strong company culture
- Unique training programs and learning opportunities.
Manager Data Science AI & Strategy,London employer: Ekimetrics
Ekimetrics is an exceptional employer that fosters a dynamic and collaborative work culture in the heart of London. With a strong emphasis on employee growth, we offer unique training programmes and mentorship opportunities, ensuring that our team members thrive both personally and professionally. Our hybrid working model, competitive benefits, and commitment to work-life balance make Ekimetrics an attractive place for those seeking meaningful and rewarding careers in data science and AI.
StudySmarter Expert Advice🤫
We think this is how you could land Manager Data Science AI & Strategy,London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works in data science. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI and data strategies. When you can demonstrate your expertise through real-world examples, it makes you stand out to potential employers.
✨Tip Number 3
Prepare for interviews by understanding the company’s needs. Research Ekimetrics and think about how your experience aligns with their goals. Tailor your responses to show how you can be the strategic partner they’re looking for.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Manager Data Science AI & Strategy,London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your experience in data science, project management, and client-facing roles. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're the perfect fit for the Data Science Manager role. Share specific examples of how you've successfully managed projects or built client relationships.
Showcase Your Technical Skills:Don’t forget to mention your technical expertise! Whether it's SQL, Python, or your experience with Gen AI, make sure we know what you bring to the table. We love seeing candidates who are passionate about data!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Ekimetrics
✨Know Your Data Inside Out
Make sure you brush up on your technical skills, especially in SQL, Python, and any relevant libraries like Pandas and Pyspark. Be ready to discuss how you've used these tools in past projects, particularly in a client-facing role.
✨Showcase Your Strategic Thinking
Prepare examples that highlight your ability to blend data science with business strategy. Think about times when you've transformed data insights into actionable strategies for clients, and be ready to share those stories.
✨Demonstrate Project Management Skills
Since this role involves managing large projects, come prepared to discuss your project management experience. Highlight specific methodologies you've used, how you handle timelines, and how you ensure successful delivery.
✨Build Rapport with the Interviewers
Remember, communication is key! Practice translating complex technical concepts into simple terms. Show your personality and engage with the interviewers; they want to see how well you can connect with clients and team members alike.
