Position – Advanced Analytics Engineer
Location : Chennai (WFO)
Experience : 7-10 Years
Shift : 2.00 PM to 11.00 PM (UK shift) and 5:30 PM to 2:30 AM (US Shift) – Rotational Basis
Key Responsibilities
- Partner with business stakeholders to understand business challenges, identify analytical opportunities, and translate requirements into scalable solutions.
- Design and develop advanced analytics models for forecasting, optimization, segmentation, classification, and predictive decision-making.
- Perform exploratory data analysis to identify patterns, trends, drivers, anomalies, and actionable business insights.
- Build, validate, deploy, and monitor machine learning and statistical models for enterprise business use cases.
- Develop analytical solutions using Python, R, SQL, Microsoft Fabric, notebooks, and related technologies.
- Create dashboards, scorecards, and self-service analytical experiences using Microsoft Power BI and Fabric.
- Collaborate with data engineers to define data requirements and ensure reliable, governed, analytics-ready datasets.
- Support AI and Generative AI initiatives by assessing business use cases and implementing appropriate analytical approaches.
- Build reusable analytics assets, feature engineering components, notebooks, templates, and frameworks.
- Document analytical methodologies, assumptions, model logic, validation results, limitations, and business recommendations.
- Present analytical insights and recommendations clearly to business and executive stakeholders.
- Apply data governance, privacy, security, and responsible AI standards throughout the analytics lifecycle.
- Mentor junior team members, participate in peer reviews, and promote analytical best practices.
- Evaluate emerging analytics, machine learning, and AI technologies that can improve business outcomes.
Required Education & Experience
Education
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, Analytics, or a related quantitative discipline.
6 to 10+ Years of Experience
- Advanced analytics, statistical analysis, or data science solution delivery.
- SQL Server, T-SQL, data analysis, and relational data modeling.
- Python or R programming for analytics and model development.
1 to 3 Years of Experience
- Microsoft Fabric and analytics workloads.
- Python, PySpark, and notebook-based development using Jupyter or Marimo.
- Machine learning, feature engineering, model validation, and model monitoring.
- AI or Generative AI solution development.
- Medallion Data Architecture and Lakehouse concepts.
- Git-based version control and CI/CD practices for analytics projects.
Core Technical Skills
Advanced Analytics & Data Science
- Predictive and prescriptive analytics
- Statistical modeling, probability, and hypothesis testing
- Regression, classification, and clustering
- Forecasting and time-series analysis
- Segmentation, optimization, and anomaly detection
- A/B testing and experiment analysis
- Feature engineering and model evaluation
Technology & Tools
- Python, R, and SQL
- Microsoft Fabric and Power BI
- PySpark
- Jupyter and Marimo notebooks
- Git and version control
- Scikit-learn or equivalent machine learning frameworks
AI & Model Lifecycle
- Generative AI applications and prompt engineering
- Model deployment, monitoring, and lifecycle management
- Responsible AI practices
- Reusable analytics solution patterns and documentation
Strongly Preferred
- Experience building enterprise-scale analytics solutions and reusable analytical products.
- Experience with workforce, hiring, recruitment, financial, or operational analytics.
- Hands-on experience delivering machine learning and AI use cases into business processes.
- Experience presenting insights and recommendations to executive stakeholders.
- Understanding of MLOps concepts and end-to-end model lifecycle management.
- Experience using AI productivity tools such as GitHub Copilot and Microsoft Copilot.
- Microsoft Fabric, Power BI, Azure Data Scientist, or related certifications.
- Strong consulting, communication, problem-solving, and data storytelling skills.
Key Competencies
- Analytical and critical thinking
- Business acumen and problem framing
- Stakeholder collaboration
- Clear written and verbal communication
- Ownership and delivery focus
- Curiosity, continuous learning, and innovation
- Mentoring and knowledge sharing
