Make sure to apply quickly in order to maximise your chances of being considered for an interview. Read the complete job description below.
Up to £60,000 + Benefits
London (3 days per week)
About the Role
Join a leading data analytics firm, with a strong reputation in the loyalty analytics space, working with top-tier clients on multiyear data science and data engineering projects. If you're passionate about data science in customer loyalty and looking for a role with direct impact, this is the place for you.
Key Responsibilities
- Work directly with clients, presenting your findings and insights to drive decision-making.
- Collaborate on clustering, regression, and time-series forecasting projects to optimize product promotions.
- Focus on building models to assess brand performance, helping clients understand which products to promote (premium vs non-premium).
- Attend monthly meetings at Welling Garden City to coordinate with the team and discuss progress.
- Use SQL and Python to analyse large datasets and deliver actionable insights to clients.
What We’re Looking For
- Experience in client-facing roles, able to communicate data-driven insights and recommendations clearly.
- Proficient in SQL and Python for data analysis and modelling.
- Strong experience with clustering, time-series forecasting, and regression techniques.
How to Apply
Please register your interest by sending your CV to Emily Burgess via the Apply link on this page.
Applied Data Scientist employer: Harnham
Join a dynamic and innovative data analytics firm that prioritises employee growth and collaboration, offering a vibrant work culture in London. With competitive salaries and benefits, including opportunities for professional development, you will have the chance to work on impactful projects with top-tier clients while enjoying a flexible work environment. This role not only allows you to apply your data science skills but also fosters meaningful connections within a supportive team dedicated to excellence in customer loyalty analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Data Scientist
✨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 Harnham!
✨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 Applied Data Scientist at Harnham.
✨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 Harnham.
✨Apply Directly through Our Website
When you find a suitable opening like Applied Data Scientist at Harnham, 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!
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.
