At a Glance
- Tasks: Lead a team of Data Scientists and deliver impactful AI solutions.
- Company: Join a growing AI-powered SaaS business transforming customer data analytics.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Work in a dynamic environment with a focus on innovation and collaboration.
- Why this job: Shape the future of AI products used by major enterprises and make a real impact.
- Qualifications: Experience in data science, machine learning, and team leadership required.
The predicted salary is between 63000 - 77000 £ per year.
Are you looking to lead and shape a Data Science function within a growing AI business? Do you enjoy combining team leadership with hands-on machine learning delivery? Would you like to influence AI products used by major enterprise organisations? We're partnered with an AI-powered SaaS business that helps enterprise organisations unlock greater value from their first-party customer data through advanced analytics, machine learning and decision intelligence. The company operates across sectors including Financial Services, Retail, Travel, Telecoms and Healthcare, delivering AI-driven products and insights to well-known enterprise clients. With multiple products already live and additional AI solutions in development, they are continuing to scale their technical capabilities. This role offers the opportunity to build and define the Data Science function while working at the centre of product, engineering and commercial decision-making.
Role
This is a Lead Data Scientist position with responsibility for leading a team of three Data Scientists while remaining hands-on across complex machine learning and analytics initiatives. You'll own modelling standards, delivery processes and data science strategy while driving commercially impactful AI solutions into production.
Responsibilities
- Lead and grow the Data Science function, defining standards, frameworks and ways of working.
- Manage, mentor and develop a team of 2 Data Scientists, under the CTO.
- Deliver advanced forecasting, customer segmentation and propensity modelling projects.
- Own end-to-end model development, validation, deployment and MLOps processes.
- Partner with Product, Engineering and Client teams to deliver production-ready Machine Learning solutions.
- Translate analytical outputs into actionable commercial recommendations for senior stakeholders.
- Drive adoption of AI tooling, LLMs and AI-assisted workflows across the function.
Salary Range: £95,000 base + benefits
Working Model: 4 days per week onsite in Central London
Tech Stack: Python, SQL, scikit-learn, pandas, NumPy, Snowflake, Databricks, Azure/AWS/GCP, XGBoost, LightGBM
Lead Data Scientist - Customer Analytics Consulting in London employer: Harnham
As a leading specialist data consultancy, we pride ourselves on fostering a collaborative and innovative work culture that empowers our Analytics Engineering Consultants to thrive. With a focus on professional development, we offer extensive growth opportunities and the chance to work on high-impact projects across diverse industries, all while enjoying the flexibility of remote work in the UK. Join us to be part of a team that values your expertise and encourages you to influence strategy and drive meaningful change for our clients.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Customer Analytics Consulting in London
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We think you need these skills to ace Lead Data Scientist - Customer Analytics Consulting in London
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 Harnham, 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 Harnham. 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 Harnham
✨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 Harnham!
✨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.
