Data Scientist (Hybrid Data Scientist & Data Engineer)
📍 Central London (Hybrid On-Site) | 💼 Financial Services
I'm looking for a Data Scientist with strong Data Engineering capabilities to join a leading financial services business in Central London on an initial 6 Month Contract basis.
The role is INSIDE of IR35. The Day Rate is yet to be defined but I think we'll be around the £600 P/D mark.
This hybrid role requires on-site presence and is ideal for professionals who can bridge the gap between data engineering and data science, owning the entire data lifecycle from ingestion to production deployment.
Key Responsibilities
- Data Engineering & Collection – Build and maintain scalable data pipelines, ensure data quality, and manage structured/unstructured datasets.
- Data Exploration & Preparation – Perform data wrangling, cleaning, and exploratory analysis to derive business-ready datasets.
- Model Development – Design, develop, and validate statistical models and machine learning solutions to solve complex financial services challenges.
- Productization & Integration – Deploy and integrate models into production systems, ensuring reliability and scalability.
- Monitoring & Maintenance – Track performance of pipelines and models, implementing retraining and performance optimization strategies.
- Communication & Visualization – Present insights clearly through dashboards, reports, and storytelling to both technical and non-technical stakeholders.
Key Skills & Experience
- Proficiency in Python and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
- Strong SQL skills and experience with data warehouses (e.g., Snowflake, BigQuery, Redshift).
- Experience with cloud platforms (AWS, GCP, or Azure) and modern data engineering tools (e.g., Airflow, dbt, Spark).
- Solid understanding of machine learning, statistical modeling, and data science best practices.
- Ability to create impactful data visualizations (e.g., Tableau, Power BI, Plotly).
- Strong problem-solving skills with the ability to communicate insights effectively.
- Experience working in financial services or another highly regulated environment is highly desirable.
