Senior Data Scientist

IMS • London, CA

14h • Remote

About The Position

The Senior Data Scientist is responsible for developing and implementing advanced data science models, machine learning algorithms, and predictive analytics solutions to drive business insights, product innovation, and operational efficiencies at IMS.

This role has been created for an exciting new project where the Senior Data Scientist will have the opportunity to work directly with our insurance partners, drawing data driven insights from large-scale datasets and performing predictive analyses focused on driver safety. This role involves creating clear data visualisations, preparing and delivering impactful presentations to communicate key findings and recommendations.
The Senior Data Scientist will work cross-functionally to create scalable, production-ready models that provide value to customers, insurers, and mobility partners. This position requires strong analytical skills, hands-on technical expertise as well as excellent communication and presentation skills.

Requirements

• 5+ years of experience in data science, machine learning, or AI model development.
• Expertise in Python, R, or Julia, with proficiency in pandas, NumPy, SciPy, scikit-learn, TensorFlow, or PyTorch.
• Experience with SQL, NoSQL, and big data technologies (Spark, Hadoop, Snowflake, Databricks, etc.).
• Strong background in statistical modelling, probability theory, and mathematical optimisation.
• Experience deploying machine learning models to production (MLOps, Docker, Kubernetes, etc.).
• Familiarity with AWS/GCP/Azure cloud ML platforms for scalable model training and inference.
• Strong problem-solving, communication, and business acumen skills.

Responsibilities

• Develop, train, and deploy machine learning models for risk scoring, behavioural analytics, fraud detection and extreme event detection.
• Optimise feature engineering, model performance, and real-time inference pipelines for large-scale datasets.
• Work on supervised, unsupervised, and reinforcement learning models to enhance decision-making.
• Leverage telematics, mobility, and insurance data to generate actionable insights and product improvements.
• Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and business opportunities.
• Ensure robustness and scalability of data science pipelines, minimising bias and improving accuracy.
• Work with big data processing frameworks (Spark, AWS, Azure) to scale data pipelines.
• Ensure efficient data wrangling, transformation, and feature selection using Python, SQL, and distributed computing.
• Optimise data workflows and cloud-based machine learning architectures, ensuring efficiency and performance.
• Directly work with customers and partners. Prepare and deliver presentations, translating data science capabilities into real-world applications.
• Collaborate with Software Engineers to deploy models via APIs, microservices, or cloud environments.
• Collaborate with the wider Engineering team to integrate machine learning models into production-grade systems.
• Stay ahead of emerging AI, ML, and data science trends, integrating innovative techniques into IMS solutions.
• Contribute to research papers, patents, and industry collaborations, positioning IMS as a thought leader in data science.

Benefits

• Flexible remote working options.
• Flexible holiday scheme (unlimited vacation) to really make the most of your time and wellbeing.
• 'Work From Anywhere' Policy - work almost anywhere in the world for 30 days per year!
• Employee Assistance Program and an enhanced maternity/paternity package
• We want to see you grow and do great things! We’re committed to your personal and professional development.
• Funded training opportunities.
• Auto-Enrolment Pension & Private Medical Insurance.
• Cycle to Work and Car Maintenance Salary Sacrifice discounts!
• Kudos Hub - a peer-to-peer recognition system, where you can recognise others using points. These points can be collected and redeemed against a huge catalogue of rewards.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed