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- Tasks: Build and refine machine learning models while collaborating with data engineers and BI developers.
- Company: Join a dynamic team at Field Sales Solutions, committed to innovation and collaboration.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by developing cutting-edge analytics solutions in a supportive environment.
- Qualifications: Experience in data science or advanced analytics, strong Python and SQL skills required.
- Other info: Embrace a culture of partnership, ownership, and determination while driving positive ROI.
The predicted salary is between 28800 - 48000 £ per year.
We’re looking for a Data Scientist to support the build and launch of our new Microsoft Fabric Lakehouse and machine learning platform. Ideal for a Junior+ / early Mid‑level DS ready to take on more responsibility and deliver real production outcomes.
What you’ll do:
- Build, test, and refine machine learning models for: activity uplift and impact measurement; ROI and value attribution; predictive forecasting; anomaly detection and alerting.
- Develop training and scoring datasets in collaboration with Data Engineers, ensuring data quality and consistency within the Delta Lakehouse.
- Perform feature engineering and help create analytics‑ready Silver and Gold datasets.
- Validate model outputs using appropriate statistical and ML evaluation techniques.
- Conduct experimentation using Fabric Notebooks (Python / PySpark) and AutoML where suitable.
- Work with BI developers to ensure model outputs flow cleanly into Power BI dashboards and reporting layers.
- Support embedding of models into production workflows, including scoring, refresh routines, and light-touch monitoring.
- Produce clear, structured documentation covering model logic, assumptions, limitations, and operational guidance.
- Participate in delivery planning and backlog refinement; work under guidance while taking ownership of defined deliverables.
- Assist with knowledge transfer to internal platform, reporting, and operational teams.
Essential Criteria:
- Commercial experience as a Data Scientist, Junior DS, or advanced Data Analyst (or relevant training).
- Strong grounding in statistics and applied analytics.
- Experience building regression, classification, forecasting, or anomaly detection models.
- Practical experience using Python for data analysis and modelling.
- Ability to work with structured business data (e.g. sales, operational or transactional datasets).
- Strong SQL skills for data exploration and validation.
- Ability to communicate analytical results clearly to non‑technical stakeholders.
- Proactive, delivery‑focused mindset with willingness to grow technical capability.
Desirable Criteria:
- Exposure to cloud analytics platforms or Lakehouse environments (e.g., Microsoft Fabric, Databricks, Synapse).
- Familiarity with notebooks, experimentation workflows, or AutoML.
- Basic understanding of PySpark or scalable data processing.
- Experience contributing to BI‑delivered analytics or embedded model outputs.
- Understanding of causal or quasi‑experimental techniques (e.g., pre/post analysis, matched controls).
- Degree in Data Science, Mathematics, Statistics, Computer Science, or a related field.
Apply today! You must be eligible to work in the UK and have a full UK Driving Licence.
Field Sales Solutions is an equal opportunities employer.
Live our company values:
- Partnership - We are transparent, open, and work together with our clients and colleagues to achieve common goals.
- Return - We drive and evaluate all activity by identifying and delivering a positive ROI.
- Ownership - We understand our role and have a sense of purpose and accountability in everything we do.
- Upstanding - We are honest, reliable, and ethical in all we do, showing professionalism and integrity always.
- Determined - we know that success requires perseverance, and we are driven to achieve.
We are PROUD to be Field Sales Solutions.
Data Scientist in Thame employer: Field Sales Solutions
Contact Detail:
Field Sales Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Thame
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning models or data analysis. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your thought process and technical skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist in Thame
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist role. Highlight your experience with machine learning models, Python, and SQL, as these are key for us.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our team. Share specific examples of your work that align with the job description.
Showcase Your Projects: If you've worked on relevant projects, whether in a professional setting or during your studies, make sure to include them. We love seeing practical applications of your skills, especially in machine learning and analytics.
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures it reaches the right people quickly!
How to prepare for a job interview at Field Sales Solutions
✨Know Your Models
Make sure you can discuss the machine learning models you've worked on in detail. Be ready to explain how you built, tested, and refined them, especially focusing on regression, classification, or anomaly detection models. This shows your practical experience and understanding of the role.
✨Brush Up on Python and SQL
Since you'll be using Python for data analysis and SQL for data exploration, it’s crucial to be comfortable with both. Prepare to answer technical questions or even solve problems on the spot. Practising coding challenges can help you feel more confident.
✨Communicate Clearly
You’ll need to explain analytical results to non-technical stakeholders, so practice simplifying complex concepts. Think about how you would present your findings in a clear and structured way, perhaps using examples from past experiences.
✨Show Your Proactive Mindset
Demonstrate your willingness to take ownership of projects and your drive to grow your technical skills. Share examples of how you've taken initiative in previous roles or projects, and be ready to discuss how you plan to continue developing in this position.
