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- Tasks: Develop and enhance forecasting models using cutting-edge Machine Learning techniques.
- Company: Join an innovative Tech company transforming hospitality and transportation with data-driven insights.
- Benefits: Enjoy remote work flexibility and a competitive salary of up to £70,000.
- Why this job: Be at the forefront of AI and ML, making impactful decisions in a dynamic environment.
- Qualifications: PhD preferred; strong experience in forecasting models and production-level Python skills required.
- Other info: This role does not offer sponsorship.
The predicted salary is between 42000 - 84000 £ per year.
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 employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨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
Prepare to showcase your experience with Python and relevant libraries like Pandas and Scikit-learn. Consider working on a personal project or contributing to open-source projects that highlight your skills in building forecasting models.
✨Tip Number 3
Network with professionals in the data science community, especially those who work in forecasting or related fields. Engaging in discussions on platforms like LinkedIn can help you gain insights and potentially get referrals.
✨Tip Number 4
Be ready to discuss how you've collaborated with both technical and non-technical stakeholders in past roles. Highlighting your communication skills and ability to translate complex data concepts into actionable insights will set you apart.
We think you need these skills to ace Senior Data Scientist
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, particularly in developing forecasting models and collaborating with stakeholders.
Showcase Relevant Projects: If you have worked on relevant projects, include them in your application. Detail your contributions, the technologies used, and the outcomes achieved, especially those related to AI and ML.
Proofread and Edit: Before submitting your application, carefully proofread all documents. Check for grammatical errors and ensure clarity in your writing. A polished application reflects your attention to detail.
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 designing a forecasting model for a specific business objective and be ready to articulate your thought process.
✨Engage with Stakeholders
This role requires collaboration with both technical and non-technical stakeholders. Prepare to discuss how you've effectively communicated complex data concepts to diverse audiences in the past, showcasing your ability to bridge the gap between data science and business needs.