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For Companies At a Glance
- Tasks: Develop and improve forecasting models for a leading tech company.
- Company: Join an innovative tech firm transforming hospitality and transportation with AI.
- Benefits: Enjoy remote work flexibility and a competitive salary up to £70,000.
- Why this job: Be at the forefront of cutting-edge machine learning in a collaborative environment.
- Qualifications: PhD preferred; strong experience in ML and forecasting required.
- Other info: No sponsorship available for this role.
The predicted salary is between 42000 - 84000 £ per year.
Remote - (Office in London) Up to £70,000
About the Role
We are working with an exciting Tech company who are seeking a Full Stack Data Scientist to join their Forecasting Algorithms team. The company's aim is to use cutting edge Machine Learning techniques to influence decision making in the hospitality and transportation space. You’ll be at the forefront of developing forecasting models, and supporting pricing strategies. This is a hands-on role where you'll own model development end-to-end—from design and testing to deployment and monitoring.
Key Responsibilities
- Lead efforts to improve the performance and scalability of deployed forecasting models.
- Design and build internal ML and forecasting libraries.
- Contribute to product planning by translating business objectives into measurable results.
- Champion best practices in model development, validation, and inference pipelines.
- Stay current with state-of-the-art techniques in AI and ML and apply them effectively.
- Work closely with technical and non-technical stakeholders.
What You’ll Bring
- PhD is highly preferred!
- Strong experience building and implementing forecasting models using modern ML techniques.
- Deep understanding of time series analysis, statistics, and forecasting methodologies.
- Production-level Python programming skills (Pandas, Polars, Scikit-learn, NumPy, SciPy).
- Comfort working in a collaborative, cross-functional environment.
Please note, this role cannot offer sponsorship at this stage.
Senior Data Scientist (United Kingdom) employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (United Kingdom)
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and forecasting techniques. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and expertise in the field.
✨Tip Number 2
Network with professionals in the data science community, especially those who work in forecasting. Attend meetups, webinars, or conferences to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Prepare to showcase your hands-on experience with Python and relevant libraries. Be ready to discuss specific projects where you've developed forecasting models, highlighting your problem-solving skills and technical abilities.
✨Tip Number 4
Understand the business context of the hospitality and transportation sectors. Research how data science impacts decision-making in these industries, so you can effectively communicate how your skills align with their goals during the interview.
We think you need these skills to ace Senior Data Scientist (United Kingdom)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with forecasting models and machine learning techniques. Use specific examples that demonstrate your skills in Python programming and time series analysis.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their goals in the hospitality and transportation sectors, and mention any relevant projects you've worked on.
Showcase Your Technical Skills: Include a section in your application that details your proficiency with tools like Pandas, Scikit-learn, and other relevant libraries. Consider providing links to any projects or GitHub repositories that showcase your work.
Highlight Collaboration Experience: Since the role involves working with both technical and non-technical stakeholders, emphasise your experience in collaborative environments. Provide examples of how you've successfully communicated complex data concepts to diverse audiences.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and the specific libraries mentioned in the job description, such as Pandas and Scikit-learn. Bring examples of forecasting models you've built and be ready to explain your approach and the results.
✨Demonstrate Your Understanding of Time Series Analysis
Since this role heavily involves time series analysis, brush up on key methodologies and be ready to discuss how you've applied them in past projects. Highlight any innovative techniques you've used to improve model performance.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about how you would approach improving a forecasting model or translating business objectives into measurable results, and be ready to articulate your thought process.
✨Emphasise Collaboration Skills
This role requires working closely with both technical and non-technical stakeholders. Be prepared to share examples of how you've successfully collaborated in cross-functional teams and how you communicate complex data concepts to non-technical audiences.
