Machine Learning Engineer - APAC

relx; Bengaluru; Vor Ort; INR 3.000.000 - 6.000.000; Vollzeit

Zusammenfassung

LexisNexis Legal & Professional, a division of RELX, is seeking a Machine Learning Engineer to accelerate our AI-driven analytics for APAC stakeholders. You will design, validate, and productionize ML models on modern data platforms, collaborating with cross-regional teams and mentoring analysts.

Role emphasizes agentic development, scalable data processing, and interpretable models, with close cooperation with data scientists and business units to deliver actionable insights.

Qualifikationen

• Master's degree preferred with a Bachelor's in Data Science, Statistics, CS or related field.
• 5+ years of experience in data and ML or closely related roles.
• Expertise in Databricks, Microsoft Fabric, and Power BI to support platform engineering.
• Strong ability to translate complex statistical concepts into actionable insights.
• Experience with cross-functional teams across regions.

Aufgaben

• Process data at scale using SQL and Python; handle missing data and normalization.
• Design and develop ML models using regression, classification, time series, and hypothesis testing.
• Implement ML algorithms prioritizing performance and interpretability.
• Conduct experiments with train/validation/test splits and cross-validation.
• Collaborate with data scientists to embed statistical insights into models.
• Optimize and productionize models on Databricks and related tooling.
• Create clear reporting and documentation for stakeholders.
• Develop autonomous workflows using Agentic development principles.
• Develop automated pipelines for data processing, model deployment, and monitoring.

Kenntnisse

SQL

Python

Databricks

Statistical analysis

ML algorithms

Data visualization

Communication

Ausbildung

Master's degree in Data Science / related field

Bachelor's degree in CS/Statistics/Math

Tools

Databricks

Power BI

Jobbeschreibung

Machine Learning Engineer

About our Company

LexisNexis Legal & Professional, a division of RELX, is a global leader in providing information-based analytics and decision tools for professional and business customers. With a presence in over 150 countries and a workforce of 11,300 employees worldwide, we are committed to delivering exceptional service and innovative solutions.

About the Team

Our team, based in the APAC region, plays a crucial role in supporting all regional functions through comprehensive reporting and data-driven insights. We are currently undergoing an exciting transition, where we are enhancing our data capabilities and embracing Agentic Development, Machine Learning, and Predictive Analytics to better support our business objectives and drive growth. Our team is composed of high-performing professionals who collaborate across business units to deliver insights that shape strategic decisions. You'll work closely with stakeholders across departments and geographies, including mentoring junior analysts and supporting organisational development initiatives.

About the role

This role directly supports our strategic shift toward machine learning, predictive analytics, and Agentic development in the region, enabling faster and more reliable delivery of insights and outcomes for APAC stakeholders on our modern data platforms.

Responsibilities

• Data Processing at Scale . Clean, transform, and join raw datasets, handling missing data, outliers, normalization, and leakage prevention using SQL and Python .
• Design and develop ML models tailored to business needs, leveraging statistical methods to ensure accuracy and reliability. Apply classical and modern techniques including regression, classification, time series analysis, and hypothesis testing to build trustworthy models.
• Implement ML algorithms with an emphasis on performance and interpretability.
• Select appropriate algorithms and use statistical techniques to optimize hyperparameters, reduce variance and bias, and manage class imbalance.
• Conduct disciplined experiments to test and validate models. Design experimental frameworks, use train validation test splits and cross validation, and interpret results with appropriate statistical significance and confidence intervals.
• Feature engineering rooted in business and statistical understanding. Create informative features through aggregation, encoding, interaction terms, and time windows; assess feature importance and stability over time.
• Model evaluation using statistically sound metrics. Evaluate with precision, recall, F1 score, ROC AUC, calibration, confusion matrices, and cost sensitive metrics appropriate to the problem.
• Collaborate with data scientists to embed statistical insights into model design and validation, ensuring robust predictive analytics and practical deployment pathways.
• Optimize and productionize models for reliability and speed. Tune hyperparameters, apply regularization and ensembling, implement monitoring for drift and performance, and manage A/B rollouts on Databricks and related tooling.
• Reporting and documentation that clearly communicates methodology, assumptions, statistical analyses, and business implications to technical and non-technical stakeholders.
• Agentic creation for intelligent solutions that designs and implements autonomous, adaptive workflows using Agentic development principles to enable self-directed decision-making and dynamic integration across business processes.
• Workflow Automation and Optimization which develops and refines automated pipelines for data processing, model deployment, and monitoring, leveraging tools such as Databricks and Microsoft Fabric to ensure scalability, efficiency, and minimal manual intervention.

Requirements

• Master's degree preferred, with a minimum of a Bachelor's degree in Data Science, Statistics, Computer Science, or a related field.
• Five or more years of experience in data and machine learning or closely related roles, demonstrating independent execution of best practices and end to end delivery from development and testing through production.
• Demonstrates expertise in our technology stack (Databricks, Microsoft Fabric, and Power BI) to support platform engineering activities, including operating, maintaining, and providing break/fix coverage for core data platforms.
• Excellent communication skills with the ability to translate technical and statistical concepts into clear, actionable insights for both technical and non-technical stakeholders.
• Ability to work effectively with cross-functional teams across regions, fostering collaboration and knowledge sharing.
• Support and encourage a high-performing team culture where treating everyone with respect is a core expectation, fostering inclusivity, trust, and accountability in all interactions.
• Must be able to hold technical conversations across SQL, Python, Data Modelling & Evaluations, Statistical Foundations, and ML Algorithms during technical interview.
• Experience in the