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Data Science with less than a year in Machine Learning & MLOps
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Irfan Mohamed is a Data Science Intern with 0.8 years of experience in Machine Learning and MLOps. He has worked on end-to-end data science and machine learning workflows, including data preprocessing, EDA, feature engineering, model training, and evaluation. His expertise includes building and deploying forecasting and regression models, implementing MLOps workflows for experiment tracking and versioning, and developing REST APIs for ML models. He is proficient in Python, SQL, and various data science tools and technologies.
Anna University
B.Tech · Artificial Intelligence and Data Science
August 1, 2021 – June 30, 2025
Bridgeon Solutions
Data Science Intern
September 1, 2025 – Present
Kerala, India
Demand Intelligence System
January 1, 2026 – January 1, 2026
Built an end-to-end demand forecasting and inventory optimization system using 40M+ transactional records. Developed LightGBM Quantile Regression models with advanced time-series feature engineering for demand uncertainty forecasting. Implemented analytical modules including price elasticity modeling and ABC-XYZ inventory segmentation. Deployed forecasting services using FastAPI, PostgreSQL, Docker, MLflow, and DVC for scalable and reproducible ML workflows.
View ProjectSpotify Music Recommender System
January 1, 2026 – January 1, 2026
Developed a content-based music recommendation system using Spotify audio features and unsupervised machine learning techniques. Built an ML pipeline with feature engineering, PCA, K-Means clustering, and cosine similarity for intelligent track recommendations. Designed modular preprocessing workflows for data cleaning, genre parsing, and feature transformation. Exposed recommendation services through FastAPI and integrated Docker, MLflow, DVC, and Git for deployment and experiment tracking.
View ProjectE-Commerce Performance Analysis
January 1, 2025 – January 1, 2025
Analyzed multi-source e-commerce datasets to identify sales trends, customer behavior, and logistics performance. Performed data cleaning, transformation, and validation using SQL and PostgreSQL workflows. Built interactive Power BI dashboards to visualize revenue, delivery delays, and customer satisfaction metrics.
View ProjectProgram with SQL
prepinsta
June 4, 2025 – Present
Achieved 94%, indicating a very strong grasp of Data Science and AI principles, with only a minor deviation from a perfect score.
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Cultural Fit Analysis
The candidate's diverse project portfolio, including demand forecasting, recommendation systems, and e-commerce analysis, demonstrates a broad interest in applying data science across different domains. The use of MLOps tools and collaborative platforms like GitHub suggests an understanding of modern development practices and teamwork. The current internship role further indicates a proactive approach to gaining real-world experience.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and a focus on end-to-end solutions, suggesting good operational fit. The English test score of 65% indicates room for improvement in communication clarity, which is crucial for presenting complex data science insights.
Scored 90%, reflecting a high level of proficiency in Power BI and data visualization, with a strong foundation in business intelligence tools.
Strengths
Limitations