Malhar Shinde
@malharshinde
AI data quality specialist turning complex model outputs into reliable training data and prompts.
ItalyWhat I'm looking for
I’m an Engineering Sciences graduate (University of Rome Tor Vergata) with hands-on experience in AI data quality, machine learning, and data analysis. I focus on making model outputs accurate, coherent, and aligned with the task—so training datasets improve where it matters.
Since 2024, I’ve worked as an AI Data Quality Specialist (freelance, remote), reviewing and evaluating AI-generated outputs for correctness and consistency. I also write and refine prompts across technical and general domains, providing structured feedback to strengthen ML model training data.
My technical foundation is reinforced by B.Sc. research applying machine learning to supercapacitor modelling and parameter estimation. I use Python (including Pandas, NumPy) and Scikit-learn for regression and EDA, and I complement this with tools like SQL, Power BI, and DAX.
I’m fluent in English (C1), Italian, and German, and I’m comfortable working in multilingual environments—especially for AI evaluation and annotation tasks. I’m seeking remote contracts in AI training data, prompt engineering, and data evaluation with companies that value quality, clarity, and measurable improvements.
Experience
Work history, roles, and key accomplishments
AI Data Quality Specialist
Freelance
Jan 2024 - Present (2 years 5 months)
Reviewed and evaluated AI-generated outputs for accuracy, coherence, and task alignment, providing structured feedback to improve ML training datasets. Wrote and refined prompts to guide model behavior across technical and general domains while supporting remote delivery.
Education
Degrees, certifications, and relevant coursework
University of Rome Tor Vergata
Master of Science (M.Sc.), Data Science
2026 -
Starting an M.Sc. in Data Science to deepen expertise in data science and quantitative modelling. Builds on an engineering foundation by combining energy systems engineering with practical data analysis.
University of Rome Tor Vergata
Bachelor of Science (B.Sc.), Engineering Sciences
Completed a B.Sc. in Engineering Sciences with a thesis applying machine learning to supercapacitor modelling, including parameter estimation. Used curve fitting, ML regression (e.g., scikit-learn), and exploratory data analysis (EDA) on real discharge data.
Availability
Location
ItalyAuthorized to work in
Job categories
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