IMS

Senior Data Scientist

IMS

full-time

Posted on:

Location Type: Hybrid

Location: London • United Kingdom

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Job Level

Senior

Tech Stack

AWSAzureCloudDockerGoogle Cloud PlatformHadoopKubernetesMicroservicesNoSQLNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

  • 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.

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.
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.
  • 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.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningfeature engineeringsupervised learningunsupervised learningreinforcement learningdata analysisdata wranglingstatistical modellingprobability theorymathematical optimisation
Soft Skills
problem-solvingcommunicationbusiness acumen