Yagyansh Bagri

CEO

United Kingdom4 yrs 8 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Lead Data Scientist with over 5 years of experience.
Expert in building scalable ML systems for production.
Strategic leader in ethical AI implementation for healthcare.

Stackforce AI infers this person is a Data Science and AI Engineering expert in Healthcare and E-commerce industries.

Contact

Skills

Core Skills

Data ScienceMachine LearningData AnalysisData EngineeringProduct Analytics

Other Skills

Python (Programming Language)Large Language Models (LLM)Vector DatabasesMicrosoft SQL ServerdbtDataBricksSQLTableauMicrosoft Power BIRStudioMixed Media MarketingA/B TestingProduct DevelopmentApache KafkaNatural Language Processing (NLP)

About

Currently sitting at the intersection of Data Science and Software Engineering. With over 5 years of experience across Healthcare, EdTech, and E-commerce, my focus is on building scalable ML systems that survive outside of a notebook and solve real business problems in production. Currently, working as a Lead Data Scientist for the NHS, where I oversee the strategic and ethical implementation of AI, including collaborating with Palantir on the Federated Data Platform (FDP). I define the technical roadmaps and governance frameworks required for enterprise-scale healthcare systems. Outside of the terminal, I believe in endurance and persistence, which is why I am currently training to swim the English Channel.

Experience

4 yrs 8 mos

Total Experience

2 yrs 2 mos

Average Tenure

4 yrs 8 mos

Current Experience

Mid yorkshire teaching nhs trust

Lead Data Scientist

Jun 2025 – Present · 11 mos · Leeds · Hybrid

Currently, architecting the AI and Data Science function for the Trust to drive operational excellence.
Federated Data Platform (Palantir): Leading the deployment of the FDP, transforming raw health data into actionable insights for patient triage and resource allocation.
Strategic Leadership: Responsible for the scalable, ethical implementation of AI, ensuring alignment with long-term Trust goals.

Python (Programming Language)Large Language Models (LLM)Vector DatabasesMicrosoft SQL ServerdbtData Science+1

Imperial college london

Data Analyst - Clinical & Education Quality

Mar 2024 – Feb 2025 · 11 mos · London Area, United Kingdom · On-site

Pipeline Engineering: Built automated data pipelines (Python/Databricks) to detect performance bottlenecks. Insights led to tangible adjustments in the medical curriculum.
Cross-Functional Leadership: Collaborated with NHS staff to map patient care challenges to educational outcomes, ensuring training aligned with clinical reality.

Python (Programming Language)DataBricksSQLTableauMicrosoft Power BIData Analysis+1

Rakuten

Product Data Scientist

Dec 2022 – Jun 2023 · 6 mos · London, England, United Kingdom · On-site

Core Focus: Leveraging high-volume e-commerce data to optimise user journeys and product features.
Product Analytics: Engineered complex SQL queries to map user behaviour pathways (funnels), identifying drop-off points and optimising the consumer lifecycle.
Data-Driven Strategy: Partnered with Product Managers to define success metrics (KPIs) for new feature launches, translating raw data into actionable engineering roadmaps.
A/B Testing: Designed and analysed experiments to validate product hypotheses, directly influencing UI/UX iterations.

A/B TestingProduct DevelopmentData EngineeringPython (Programming Language)Machine LearningData Analysis+1

Crowdcube

Angel Investor

Sep 2021 – Present · 4 yrs 8 mos · London Area, United Kingdom

Building a portfolio of 100 startups. Current investments include Mous, MoneyBox, Plum, Eslando and FreeTrade (Acquired).

Datacove

Founding Data Scientist

Sep 2021 – Oct 2023 · 2 yrs 1 mo · London Area, United Kingdom · On-site

Joined as the first technical hire to architect the company’s data infrastructure and machine learning capabilities.
Predictive Ad Engine: Engineered a predictive model to forecast marketing performance and optimise Return on Ad Spend (ROAS). Utilised historical data to predict campaign outcomes before launch.
Pipeline Architecture: Built the end-to-end data pipelines to ingest real-time advertising metrics, feeding the prediction models for automated reporting.
Recruitment Algorithms: Developed the core candidate-matching logic, reducing manual screening time by automating the candidate-to-role scoring process.

RStudioPython (Programming Language)Mixed Media MarketingA/B TestingdbtMachine Learning+1

Ddn storage

Data Analyst - Quantitative ML Engineer

Sep 2021 – Oct 2022 · 1 yr 1 mo · Edinburgh, Scotland, United Kingdom · Remote

Core Focus: Engineering NLP models to extract market signals from unstructured social media data.
Sentiment Analysis Engine: Developed and tuned Natural Language Processing (NLP) models to scrape and analyse high-velocity social media streams (Twitter/Reddit), quantifying market sentiment.
Price Prediction: Correlated sentiment scores with cryptocurrency market data to build predictive time-series models for price forecasting.
Distributed Engineering: Delivered a fully functional prediction product within 12 months, collaborating effectively within a fully remote, distributed engineering team.

Python (Programming Language)Apache KafkaNatural Language Processing (NLP)API DevelopmentMicrosoft Power BIMachine Learning+1

Mckinsey & company

Solve It 2021 Finalist

Mar 2021 – Apr 2021 · 1 mo · London, England, United Kingdom · Remote

Selected as a finalist (Top 10%) from a competitive pool of 50+ teams to address strategic operational challenges for a non-profit client.
Strategic Problem Solving: Applied McKinsey’s consulting frameworks to diagnose organisational bottlenecks and propose data-backed solutions.
Executive Presentation: Developed and presented a comprehensive strategy deck to a panel of McKinsey partners and industry experts.
Team Leadership: Coordinated a cross-functional team under tight deadlines to deliver a cohesive business case.