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Rena Sebastian

@renasebastian

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Data science intern at Mercedes-Benz CAC, forecasting workforce demand and analyzing historical workforce data.

Netherlands

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At Mercedes-Benz CAC, I support the transition to an integrated workforce management setup using CCMath alongside Genesys Cloud. I analyze historical workforce data and forecast demand and workload to support workforce planning.

At Goodlight AI, I support AI solutions for grocery retailers, including market basket analysis, customer email analysis, loyalty programme data, and conversational agents. At Indian Institute of Remote Sensing (IIRS), ISRO, I developed an automated framework for detecting infested Shorea robusta trees from satellite imagery, achieving a ROC-AUC of 0.9950.

At Celebal Technologies, I applied data preprocessing, exploratory analysis, and machine learning to structured and unstructured data, contributing to an approximately 20% improvement in decision-making efficiency. Earlier, at Black Box, I developed call-volume forecasting models, with SARIMA achieving 92% accuracy; I also built a medical voice assistant that achieved over 90% accuracy in handling medical queries.

Experience

Work history, roles, and key accomplishments

Current

WFM Forecasting Intern

Current

Mercedes-Benz CAC

Sep 2026 - Present (1 month)

Supporting the transition from Genesys Cloud to an integrated workforce management setup using CCMath. Working on workforce management forecasting and analysis, including analysing historical data, forecasting demand and workload, and supporting data-driven planning.

Genesys Cloud CCMath Workforce Management Forecasting Data Analysis

Current

Machine Learning Intern

Current

Goodlight AI

Aug 2026 - Present (2 months)

Supporting the development and application of AI solutions for grocery retailers, focusing on using customer and retail data to improve business decision-making and customer engagement. Working on use cases including market basket analysis, customer email analysis, loyalty programme data, and AI-powered customer-facing agents.

Machine Learning AI Data Analysis Basket Analysis Customer Engagement

Artificial Intelligence Intern

Indian Institute of Remote Sensing (IIRS), ISRO

Feb 2026 - May 2026 (3 months)

Developed an automated RF-GEOBIA framework for canopy-level detection of Hoplocerambyx spinicornis-infested Shorea robusta trees using PlanetScope satellite imagery. Built an end-to-end Python pipeline incorporating Dark Object Subtraction normalisation, SLIC-MMTD adaptive superpixel segmentation, and a 28-feature Random Forest classifier, achieving a ROC-AUC of 0.9950.

Python Random Forest Remote Sensing Image Processing Machine Learning GEOBIA

Data Science Intern

Celebal Technologies

Jun 2025 - Aug 2025 (2 months)

Applied data preprocessing, exploratory analysis, machine learning model development, and model evaluation using Python, pandas, NumPy, and scikit-learn. Collaborated with mentors and cross-functional teams to derive insights from structured and unstructured data, contributing to an approximately 20% improvement in decision-making efficiency.

Python Pandas NumPy scikit learn data preprocessing Machine Learning Data Analysis

Data Science Intern

Black Box

Aug 2024 - Sep 2024 (1 month)

Developed predictive models using SARIMA, ARIMA, Prophet, Random Forest, and Linear Regression for daily call-volume forecasting, with SARIMA achieving the highest accuracy of 92%. Performed exploratory data analysis and time-series forecasting using Python, statsmodels, and scikit-learn to support call-centre resource planning and workforce optimisation.

Python SARIMA ARIMA Prophet Random Forest Linear Regression Time series Forecasting Statsmodels scikit learn

Education

Degrees, certifications, and relevant coursework

Radboud University

MS, Computing Science

2026 -

Pursuing an MS in Computing Science with a specialization in Data Science and Artificial Intelligence, covering machine learning, AI, data science, statistical analysis, programming, algorithms, and computational methods.

SRM University

B.Tech., Computer Science Engineering

2022 - 2026

Grade: 9.07 / 10

Completed a B.Tech. in Computer Science Engineering with a specialization in Data Science and Artificial Intelligence, covering computer science, data science, AI, machine learning, programming, algorithms, databases, statistics, and data analysis.