Title: Lead Data Scientist
Location: Bedfordshire – Hybrid – 2 days a week in office
Salary: £80,000 + Bonus/Benefits
Contact: harry.bartlett@forsythbarnes.com
Brief Overview:
Forsyth Barnes are working with major retail and service provider across the UK, Ireland and US who are in a rapid growth phase and seek a to onboard a Lead Data Scientist to identify and unlock the potential of its data assets through advanced analytics and model-based solutions.
The successful candidate will work closely with stakeholders to create hypotheses, analyse complex datasets, and design data-driven solutions. They will also collaborate with the Data Engineering and Architecture teams to ensure the effective use of the data platform for delivering business focused results.
Lead Data Scientist - Responsibilities:
* Developing and testing hypotheses that could meaningfully impact business and operational performance.
* Extracting insights from large and varied datasets (structured and unstructured).
* Building statistical models to identify trends, patterns, and actionable insights.
* Applying advanced analytics across product lifecycles, driving decisions at each stage.
* Translating complex technical data into clear recommendations for stakeholders.
* Designing and developing interactive dashboards using Power BI to deliver real-time insights.
Lead Data Scientist - Required Skills/Experience:
* Developing and testing hypotheses that could meaningfully impact business and operational performance.
* Extracting insights from large and varied datasets (structured and unstructured).
* Building statistical models to identify trends, patterns, and actionable insights.
* Applying advanced analytics across product lifecycles, driving decisions at each stage.
* Translating complex technical data into clear recommendations for stakeholders.
* Designing and developing interactive dashboards using Power BI to deliver real-time insights.
* Data Visualisation: Proficiency in creating impactful visualisations (e.g., Power BI).
* Statistical Modelling: Experience in regression techniques
* Machine Learning: Hands-on experience with scalable ML pipelines
* Programming: Strong proficiency in Python; experience with Java and C is beneficial.
* Azure Data Tools: Familiarity with Azure applications (MS Fabric Stack preferred).