Data Scientist

Responsibilities

We are representing a confidential cloud infrastructure organization seeking a Data Scientist to join their reliability platform team in London. In this role, you will work at the intersection of data science and production systems, deploying advanced statistical models and machine learning methodologies directly within operational environments.

You will collaborate closely with engineering and infrastructure teams to optimize GPU utilization, workload scheduling, and system efficiency in real time. Your work will involve designing experiments, analyzing large-scale system telemetry data, and building predictive and optimization solutions that are tightly integrated into production workflows. This position blends hands-on deployment with analytical rigor, turning complex infrastructure data into measurable improvements in performance and cost.

The team is building a layered reliability platform spanning telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. You will partner with fleet, infrastructure, and platform teams to embed data science directly into production environments—improving cluster reliability, increasing effective utilization, reducing mean time to recovery, and protecting uptime and revenue.

What We're Looking For

Required Qualifications:

• MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related quantitative field
• 8+ years applying statistical modeling or machine learning to large-scale datasets
• Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow)
• Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing)
• Experience working with distributed data systems (Spark, Ray, Dask, or similar)
• Proficiency in SQL and working with large-scale structured datasets
• Experience building, deploying, and maintaining predictive models in production environments
• Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning)
• Experience working with time-series data and performance telemetry
• Ability to translate analytical insights into production-ready systems and workflows
• Strong collaboration skills and ability to work cross-functionally in fast-paced environments

Preferred Qualifications:

• PhD with published research in systems optimization, distributed computing, ML systems, or performance modeling
• Experience with GPU workloads, distributed training, or AI infrastructure
• Familiarity with Kubernetes, containerized workloads, or cloud-native systems
• Experience deploying reinforcement learning or adaptive scheduling systems in production
• Background in capacity planning, forecasting, or resource allocation modeling
• Contributions to open-source ML or systems projects

Ideal candidates will:

• Love uncovering hidden failure patterns in massive, noisy infrastructure datasets
• Enjoy working directly with engineering teams to deploy solutions that have immediate real-world impact
• Be curious about building autonomous, agentic systems that investigate and explain system behavior
• Have expertise in reinforcement learning, predictive modeling, or large-scale data analysis

How We Work With You

Our talent team at Get A Job.ai partners with leading technology organizations to connect exceptional data science professionals with high-impact opportunities. When you apply through our platform, a dedicated recruiter will review your background and conduct an initial screening to understand your experience and career goals.

If your profile aligns with our client's requirements, we will submit your candidacy for consideration and guide you through each stage of the interview process. We ask that candidates do not contact the client directly, as all communication and coordination will be managed through Get A Job.ai to ensure the best possible experience for everyone involved.

Pay

Compensation details will be discussed during the screening process and are competitive with the London market for senior data science roles at leading technology companies.

Equal Opportunity: Get A Job.ai is committed to fostering an inclusive recruiting process. We welcome applications from candidates of all backgrounds and work with clients who share our commitment to building diverse teams.