A strategic team leader transitioning into Data Science and AI Engineering, bringing 5 years of ownership-driven decision-making in operations and leadership to the discipline of turning data into business outcomes.
I am Er. Maharshi Shukla, a Data Scientist and AI Engineer based in Ahmedabad, India. With a background in Electrical Engineering and over 5 years of professional experience across operations, sales, and team leadership, I bring a perspective to data problems grounded in real-world constraints and business outcomes, not just technical correctness.
I completed the Data Scientist & AI Engineering program at Datamites (Nov 2025 – Jun 2026) and hold a course-completion certification as an AI Engineer. My IABAC and NASSCOM certification exams are scheduled once my current client project wraps up.
I'm currently a Data Science & AI Engineering Intern at Rubixe, where I own the full lifecycle of capstone ML projects, two of which have already been evaluated with Grade A. Before this, as Team Leader at TTEC India Pvt. Ltd., I turned a team ranked second-last on CSAT into the #1-ranked team in our branch, using the same instincts I now apply to modelling: read the data, form a hypothesis, act, and measure the result.
Beyond formal projects, I've also become genuinely skilled at directing AI systems to get precise, intentional results, using tools like Claude, ChatGPT, Gemini, and Antigravity to build working software and creative work from a plain-language description of what I want.
Every role below is framed the way I approach data: what was the problem, what did I do, what changed.
Capstone work from my Rubixe internship, plus independent builds.
Binary classifier on accelerometer sensor data. Time-series feature engineering with Random Forest & SVM, benchmarked via stratified cross-validation.
Regression model predicting salaries across Texas regions, using outlier treatment, encoding, and ensemble hyperparameter tuning for robust generalisation.
Content-based filtering engine using TF-IDF vectorisation & cosine similarity on genres, cast, and descriptions to surface ranked recommendations.
CNN for 0–9 digit classification using convolution, pooling, batch normalisation and dropout regularisation.
Clustering on player attributes for role-fit profiling, with ranking metrics and visualisations for squad optimisation.
Self-built with AI-assisted prompt engineering: login-based DS/AI quiz platforms with scoring, leaderboards, and a review bank of wrong answers, plus an extended scientific calculator with more functions and keys than a standard one, built for faster everyday calculations. Not yet deployed; happy to share a live walkthrough.
Directed a realistic short action/superhero film end to end purely through prompting: sequencing many generated images into a coherent, consistent narrative and getting precise, intended results from the model at each step. Alongside this, I regularly run smaller prompting explorations on personal-interest topics, refining prompts until the output matches what I actually had in mind.
I'm an immediate joiner, actively looking for Data Scientist, AI/ML Engineer, or Data Analyst roles where I can turn data into decisions that matter.
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