Advanced Analytics Engineer

Threatxintel; Chennai District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Threatxintel is seeking an Advanced Analytics Engineer to join the Enterprise Data & Analytics team. The role involves solving complex business problems using advanced analytics, statistical modeling, machine learning, AI, and data visualization.

The ideal candidate will work closely with business stakeholders, data engineers, and leadership teams to develop predictive models, analytical solutions, dashboards, and intelligent decision-support systems.

Qualifications

• Advanced analytics and statistical analysis
• Predictive and prescriptive analytics
• Regression, classification, and clustering
• Forecasting and time-series analysis
• Segmentation and anomaly detection
• Hypothesis testing and A/B testing
• Feature engineering and model evaluation

Responsibilities

• Translate business requirements into scalable analytics and data science solutions.
• Perform Exploratory Data Analysis (EDA) to identify trends, patterns, anomalies, and business drivers.
• Develop predictive and prescriptive analytics models for forecasting, classification, segmentation, optimization, and decision-making.
• Build, validate, deploy, monitor, and maintain machine learning and statistical models.
• Develop analytics solutions using Python, R, SQL, PySpark, Microsoft Fabric, and notebooks.
• Build dashboards, scorecards, and self-service analytics using Power BI and Microsoft Fabric.
• Perform feature engineering, model evaluation, experimentation, and statistical analysis.
• Support AI and Generative AI initiatives, including business use-case assessment and prompt engineering.
• Work with data engineering teams to define data requirements and develop analytics-ready datasets.
• Apply Medallion Architecture and Lakehouse concepts in analytics solutions.
• Create reusable notebooks, frameworks, analytical components, and templates.
• Document methodologies, assumptions, model logic, validation results, limitations, and recommendations.
• Present analytical findings and recommendations to business and executive stakeholders.
• Follow data governance, privacy, security, and Responsible AI practices.
• Mentor junior team members and contribute to analytics best practices.

Skills

Advanced analytics

Statistical analysis

Predictive analytics

Prescriptive analytics

Time-series analysis

Hypothesis testing

A/B testing

Feature engineering

Model evaluation

Data storytelling

Tools

Python

R

SQL

PySpark

Microsoft Fabric

Power BI

Jupyter notebooks

Marimo

Scikit-learn

Git

Job description

Job Summary

We are looking for a highly skilled Advanced Analytics Engineer to join our Enterprise Data & Analytics team. The role involves solving complex business problems using advanced analytics, statistical modeling, machine learning, AI, and data visualization.

The ideal candidate will work closely with business stakeholders, data engineers, and leadership teams to develop predictive models, analytical solutions, dashboards, and intelligent decision-support systems.

Key Responsibilities

• Translate business requirements into scalable analytics and data science solutions.
• Perform Exploratory Data Analysis (EDA) to identify trends, patterns, anomalies, and business drivers.
• Develop predictive and prescriptive analytics models for forecasting, classification, segmentation, optimization, and decision-making.
• Build, validate, deploy, monitor, and maintain machine learning and statistical models.
• Develop analytics solutions using Python, R, SQL, PySpark, Microsoft Fabric, and notebooks.
• Build dashboards, scorecards, and self-service analytics using Power BI and Microsoft Fabric.
• Perform feature engineering, model evaluation, experimentation, and statistical analysis.
• Support AI and Generative AI initiatives, including business use-case assessment and prompt engineering.
• Work with data engineering teams to define data requirements and develop analytics-ready datasets.
• Apply Medallion Architecture and Lakehouse concepts in analytics solutions.
• Create reusable notebooks, frameworks, analytical components, and templates.
• Document methodologies, assumptions, model logic, validation results, limitations, and recommendations.
• Present analytical findings and recommendations to business and executive stakeholders.
• Follow data governance, privacy, security, and Responsible AI practices.
• Mentor junior team members and contribute to analytics best practices.

Required Skills

Advanced Analytics & Data Science

• Advanced analytics and statistical analysis
• Predictive and prescriptive analytics
• Regression, classification, and clustering
• Forecasting and time-series analysis
• Segmentation and anomaly detection
• Hypothesis testing and A/B testing
• Feature engineering and model evaluation

Technical Skills

• Python / R / SQL
• SQL Server and T-SQL
• PySpark
• Microsoft Fabric
• Power BI
• Jupyter or Marimo notebooks
• Scikit-learn or equivalent ML frameworks
• Git and version control
• CI/CD for analytics projects

AI & ML

• Machine learning model development and validation
• Model deployment, monitoring, and lifecycle management
• Generative AI applications
• Prompt engineering
• Responsible AI
• MLOps concepts

Experience Requirements

• 610+ years of experience in advanced analytics, data science, statistical analysis, or analytics solution delivery.
• 13 years of hands-on experience with Microsoft Fabric, PySpark, notebook-based development, machine learning, AI/GenAI, and Lakehouse/Medallion Architecture.
• Experience delivering enterprise-scale analytics or data science solutions.
• Experience translating business problems into analytical solutions.
• Experience working with cross-functional stakeholders and presenting insights to leadership.

Preferred Experience

• Workforce, recruitment, hiring, financial, or operational analytics.
• Hands-on implementation of ML/AI solutions within business processes.
• Enterprise analytics products and reusable analytics frameworks.
• MLOps and end-to-end model lifecycle management.
• GitHub Copilot, Microsoft Copilot, or similar AI productivity tools.
• Microsoft Fabric, Power BI, or Azure Data Scientist certifications.

Key Competencies

• Strong analytical and critical-thinking skills
• Business problem-solving and consulting mindset
• Excellent stakeholder communication
• Data storytelling and presentation skills
• Ownership and delivery focus
• Innovation and continuous learning
• Mentoring and knowledge sharing

Keywords

Advanced Analytics | Data Science | Python | R | SQL | T-SQL | Microsoft Fabric | Power BI | PySpark | Machine Learning | Generative AI | GenAI | Statistical Modeling | Predictive Analytics | Prescriptive Analytics | Forecasting | Time Series | Scikit-learn | MLOps | Lakehouse | Medallion Architecture | Azure | Git | CI/CD | Jupyter | Marimo