Help & Supportcareers@gravityer.com
MLOps Engineer with 6+ years in Data Science & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior Data Analyst with over two years' experience delivering data-driven solutions at Thames Water, backed by previous analytical roles across technology, insurance and consulting. Databricks Machine Learning Associate certified with hands-on experience building end-to-end machine learning pipelines using Python, SQL, Spark, MLflow and Databricks, including automated data processing, model deployment, CI/CD and monitoring. Passionate about applying MLOps best practices to deliver reliable, production-ready machine learning solutions and seeking to transition into an MLOps Engineer role.
University of Kent
BSc · Financial Economics
August 1, 2015 – June 30, 2017
Thames Water
Senior Data Analyst
July 1, 2024 – Present
India
Sony Europe
Process Manager
September 1, 2022 – July 1, 2024
India
Hastings Direct
MI Analyst
June 1, 2021 – September 1, 2022
India
Willis Towers Watson
Actuarial Analyst
September 1, 2019 – June 1, 2021
India
Telco Churn Prediction MLOps Pipeline
June 28, 2026 – Present
Engineered production-grade ML pipeline on Databricks demonstrating end-to-end model lifecycle from preprocessing through real-time inference and continuous monitoring. Implemented Delta Lake data versioning enabling reproducible train/test snapshots and incremental monitoring. Designed MLflow experiment tracking with model registry aliases, enabling seamless model swaps in production without client-side config changes. Built REST inference endpoint with low latency, auto-scaling (scale-to-zero), and real-time model monitoring. Implemented deterministic A/B testing framework using customer IDs, ensuring 50/50 traffic split with same customer consistently receiving same model variant. Deployed Lakehouse quality monitors with automated drift detection on inference logs, detecting feature/prediction distribution shifts and data quality issues in production. Configured via Databricks Bundles with multi-environment support (dev/acc/prd).
View ProjectDatabricks Certified Machine Learning Associate
Databricks
January 1, 2026 – January 1, 2028
Cultural Fit Analysis
The candidate shows a clear passion for applying MLOps best practices and a desire to transition into an MLOps Engineer role, aligning well with the target position. The diverse project experience, particularly the detailed MLOps pipeline, demonstrates initiative and a proactive approach to skill development. The career progression from Actuarial Analyst to Senior Data Analyst, with increasing exposure to data engineering and ML initiatives, suggests adaptability and a continuous learning mindset. The breadth of skills across data analysis, BI, and ML engineering indicates a versatile profile.
Soft Skills & Operational Fit
The candidate's resume highlights experience collaborating with technical and business stakeholders, presenting technical findings, and translating complex datasets into actionable insights. This indicates good communication and collaboration skills, which are crucial for an MLOps Engineer working across data science, engineering, and business teams. The experience in managing marketing data processes and improving data quality also suggests an operational mindset and attention to detail.