Machine Learning Engineer - APAC

LexisNexis Risk Solutions; Bengaluru; On-site; INR 1,800,000 - 2,500,000; Full time

Benefits offered by this job

Flexible working arrangements

Benefits for you and your family

Access to learning and development

Job summary

LexisNexis Legal & Professional in APAC region is expanding its data capabilities with machine learning and predictive analytics. The role focuses on building scalable ML models, conducting disciplined experiments, and delivering data-driven insights to stakeholders across regions.

You will collaborate with data scientists, mentor analysts, and contribute to autonomous, adaptive workflows using Agentic development principles to enable self-directed decision-making.

Qualifications

• 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, delivering end-to-end from development to production.
• Expertise in Databricks, Microsoft Fabric, and Power BI to support platform engineering activities.

Responsibilities

• Data Processing at Scale using SQL and Python to clean, transform, and join raw datasets.
• Design and develop ML models tailored to business needs with robust validation.
• Apply regression, classification, time series analysis, and hypothesis testing to build trustworthy models.
• Implement ML algorithms with emphasis on performance and interpretability.
• Experiment with hyperparameters, reduce variance and bias, and handle class imbalance.
• Design experimental frameworks with train/validation/test splits and cross-validation.

Skills

SQL

Python

Statistical analysis

Experimentation

Model evaluation

Feature engineering

Hyperparameter tuning

Cross-validation

Education

Master's degree preferred

Bachelor's degree in Data Science, Statistics, Computer Science, or related field

Tools

Databricks

Microsoft Fabric

Power BI

MLflow

Power Apps

Job description

Machine Learning Engineer

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 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 following areas will be highly advantageous:
  • NLP (text preprocessing, topic modeling, classification, sentiment analysis)
  • Agentic models & Generative AI
  • Databricks Microsoft Fabric (model administration & maintenance)
  • Workflow automation
  • ETL pipelines
  • PowerApps
  • MLflow
  • Data pipeline orchestration
  • Version control
  • CI/CD
  • Model monitoring
  • Power BI

Work in a way that works for you

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

Working for you

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

• Flexible working arrangements
• Benefits for you and your family
• Access to learning and development resources

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

About the Business

LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

USA Job Seekers: EEO Know Your Rights. RELX is a global provider of information-based analytics and decision tools for professional and business customers, enabling them to make better decisions, get better results and be more productive. Our purpose guides our actions beyond the products that we develop. It defines us as a company. Every day across RELX our employees are inspired to undertake initiatives that make unique contributions to society and the communities in which we operate.