About the Role

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

You will work closely with business stakeholders, data engineers, and leadership teams to transform data into actionable insights, predictive models, and intelligent decision-support solutions.

Key Responsibilities

Design and develop predictive and prescriptive analytics solutions.
Perform exploratory data analysis to identify trends, patterns, anomalies, and business drivers.
Build, validate, deploy, and monitor machine learning and statistical models.
Develop analytics solutions using Python, R, SQL, Microsoft Fabric, PySpark, and notebooks.
Create dashboards and analytical experiences using Power BI and Microsoft Fabric.
Perform forecasting, segmentation, classification, clustering, optimization, and anomaly detection.
Implement feature engineering and model evaluation techniques.
Support AI and Generative AI use cases, including prompt engineering.
Work with data engineers to develop reliable, governed, analytics-ready datasets.
Apply Medallion Architecture and Lakehouse concepts.
Follow Git-based version control and CI/CD practices.
Document model methodologies, assumptions, validation results, and recommendations.
Present analytical insights to business and executive stakeholders.
Mentor junior team members and contribute to analytics best practices.

Required Skills

6–10+ years of experience in Advanced Analytics / Data Science / Statistical Analysis.
Strong SQL Server, T-SQL, SQL, and relational data modeling experience.
Strong hands-on experience with Python or R.
Experience with Machine Learning, Statistical Modeling, Forecasting, and Predictive Analytics.
Experience with Microsoft Fabric and Power BI.
Experience with PySpark and notebook-based development.
Knowledge of feature engineering, model validation, and model monitoring.
Experience with Generative AI / AI solution development.
Knowledge of Medallion Data Architecture and Lakehouse concepts.
Experience with Git and CI/CD.
Strong communication, stakeholder management, analytical thinking, and data storytelling skills.

Preferred

Enterprise-scale analytics solution development.
Workforce, recruitment, financial, or operational analytics experience.
MLOps and end-to-end model lifecycle experience.
Experience presenting insights to executive stakeholders.
GitHub Copilot / Microsoft Copilot experience.
Microsoft Fabric, Power BI, Azure Data Scientist, or related certifications.

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, Analytics, or a related quantitative discipline.

Interested candidates can apply with their updated profile/CV.