SQL for data Science

Microsoft Certified: Power Platform Fundamentals

Microsoft Certified: Azure Fundamentals

Python

PwC Switzerland - Power BI Job Simulation

Python Problem solving

AWS APAC - Solutions Architecture Job Simulation

British Airways - Data Science Job Simulation

Accenture North America - Data Analytics and Visualization Job Simulation

How To Visualize Your Data Using Microsoft Powerpoint

Bachelor of Engineering - BE

Completed an intensive PM simulation for a live strategy RPG mobile
game — focused on data-driven product decisions.
Key contributions:
→ Defined and selected KPIs for a mobile game product using
   structured data analysis and SQL-derived insights
→ Translated complex business data into clear, decision-ready
   recommendations for non-technical leadership
→ Produced a full product performance presentation with metric
   definitions, trend analysis, and strategic recommendations
This experience sharpened my ability to own the "why" behind
product metrics — not just report numbers, but drive decisions with them.
Skills: KPI Definition · Product Analytics · SQL · Stakeholder Communication · Mobile Product

Product Management

Gained practical experience in data analysis and statistical modeling by working on diverse projects involving large datasets, utilizing Python, R, and SQL to derive actionable insights and build predictive models.
Skilled in implementing machine learning algorithms using frameworks such as TensorFlow, Scikit-learn, and Keras. Developed data visualizations with tools like Tableau and Matplotlib to effectively communicate complex data insights to stakeholders.

Data scientist Intern

Led end-to-end development of a production-grade RAG-based document
intelligence pipeline — owning both the product definition and technical
execution.
Key contributions:
→ Defined product requirements and success metrics for an AI document
   processing system, improving information retrieval accuracy by 25% over baseline
→ Architected REST API integrations connecting UI, cloud (Azure AI Services),
   and LLM inference layers — reducing data pipeline latency significantly
→ Owned model evaluation framework in Python/TypeScript, standardizing
   structured output validation and cutting manual review overhead by ~40%
→ Drove cross-functional alignment between engineering and business
   stakeholders on AI feature scope and delivery timelines
Tech: Azure AI Services · LLM Fine-tuning · RAG · Python · TypeScript · MySQL

Data Scientist Intern

Built real-time data infrastructure that powered product decisions
at a fintech company operating within JPMorgan's ecosystem.
Key contributions:
→ Built a real-time data visualization dashboard using React.js
   and TypeScript with cloud API integration and low-latency rendering
→ Collaborated in Agile/Scrum sprints — triaging bugs, shipping
   feature enhancements, and iterating on UX based on stakeholder feedback
→ Bridged engineering and product teams — translating technical
   constraints into product decisions
Skills: React.js · TypeScript · Cloud APIs · Agile · Scrum · Data Visualization

Software Engineer Intern

Worked directly on improving LLM output quality at scale — a core
responsibility of any AI PM managing a model-based product.
Key contributions:
→ Evaluated and benchmarked LLM outputs across code generation,
   logic, and reasoning — identifying systematic failure modes
→ Designed evaluation rubrics and prompt structures adopted
   as quality benchmarks across the team
→ Built structured feedback loops that measurably improved
   model accuracy and consistency in production
→ Developed deep expertise in prompt engineering, model behavior
   analysis, and AI quality assurance
This role taught me how to think about AI product quality from the
inside — not just what users see, but why models fail and how to fix it.
Skills: Prompt Engineering · LLM Evaluation · AI Quality Assurance · Model Benchmarking

AI Training Coding Expert. Intern

Built and deployed supervised learning models for image classification and sentiment analysis using TensorFlow and Scikit-learn, achieving measurable accuracy benchmarks on real-world datasets. Executed full data preprocessing pipelines — cleaning, feature engineering, and exploratory data analysis — to ensure high-quality model inputs. Developed data visualizations in Matplotlib to surface insights from model outputs and communicate findings to non-technical reviewers. Bridged the gap between raw data and production-ready ML: from messy inputs to deployed, interpretable models.

Machine Learning Intern

Data Scientist intern

Ai Product builder 0 --> 1

github

Know about Abhishek R's work experience, education, bootcamps, certifications, and much more. Abhishek R