Rakisha R

Aspiring Machine Learning Engineer/Data Science Engineer

Nagercoil, India 0+ yrs exp 81 · Excellent

About

Aspiring Machine Learning Engineer/Data Science Engineer with strong foundations in Python, SQL, and Data Science algorithms. Experienced in building ML models, automating data pipelines, and developing end-to-end applications using frameworks like TensorFlow, React, and Spring Boot. Skilled at translating data into actionable insights using Power BI and eager to contribute to ML model development, deployment, and GenAI experimentation.

Skills & Expertise (19)

Python Intermediate

6.5/10

Years Exp

Machine Learning Intermediate

6.5/10

Years Exp

SQL Intermediate

6.5/10

Years Exp

Pandas Intermediate

6.0/10

Years Exp

Exploratory data analysis Intermediate

6.0/10

Years Exp

Data Transformation Intermediate

6.0/10

Years Exp

Data Cleaning Intermediate

6.0/10

Years Exp

scikit-learn Intermediate

6.0/10

Years Exp

NumPy Intermediate

6.0/10

Years Exp

TensorFlow Intermediate

5.5/10

Years Exp

PyTorch Intermediate

5.5/10

Years Exp

Power BI Intermediate

5.0/10

Years Exp

Snowflake Intermediate

5.0/10

Years Exp

UiPath Intermediate

4.5/10

Years Exp

Docker Intermediate

4.0/10

Years Exp

AWS Intermediate

4.0/10

Years Exp

React Beginner

3.5/10

Django Beginner

3.5/10

Spring Boot Beginner

2.5/10

Work Experience

Intelligent Automation/Data Science Intern

Nissan Digital India LLP

Jul 2025 - Jan 2026

Built Python-based automation solutions, including a Profit Share Bot and an internal license allocation & approval web application, improving operational efficiency. Performed event-based volume analysis on large-scale automotive datasets using Snowflake, including FMC vs non-FMC classification, yearly volume consolidation, and ratio-based KPI computation. Created analytics-ready datasets using optimized Snowflake SQL queries, views, and stored procedures to support reporting and data-driven decisions.

Intern

PRODIGY INFOTECH

May 2024 - Jun 2024

Analyzed fast-moving consumer product sales data using Python and SQL to identify demand patterns and manufacturing trends. Built sales forecasting insights by performing data cleaning, aggregation, and trend analysis on historical sales data. Generated data-driven insights to support production planning and inventory optimization.