I believe in building with curiosity, leading with empathy, and solving with data.
Dian Yue Josef Zhu

Dian Yue Josef Zhu

Data Scientist | AI/ML Consultant | Computational Biology Researcher

Co-Founder at JZMB GmbH | Building AI-powered solutions for e-commerce and healthcare

Get In Touch View My Work

About Me

I'm a data scientist and AI consultant with a passion for building intelligent systems that solve real-world problems. Currently pursuing my MSc in Computational Biology at Weill Cornell Medicine while co-founding JZMB GmbH, where I develop AI-powered solutions for e-commerce and personalized recommendations.

With extensive experience at companies like Johnson & Johnson, Swarovski, and Amazon, I've led teams in deploying machine learning models, building analytics pipelines, and driving data-driven decision making. My work spans predictive analytics, anomaly detection, dynamic pricing, and spatial transcriptomics research.

I'm fluent in German and Chinese, conversational in French, and always excited to tackle challenging problems at the intersection of data science, AI, and biology.

Work Experience

Co-Founder & Managing Director

Oct 2023 - Present

JZMB GmbH, Zurich

  • Offering AI/ML consulting: Provide product recommendation and algorithm design services to external clients in e-commerce domains.

Senior Product Data Analyst

Mar 2023 – Aug 2024

Johnson & Johnson, Zug

  • Led an international team of 6 analysts in the Digital Transformation Office (DTO) to drive data harmonization across supply chain and manufacturing, enabling faster reporting for 300+ stakeholders worldwide.
  • Initiated scalable analytics pipelines in Azure and Databricks, connecting outputs to a Neo4J Knowledge Graph to improve traceability and enable predictive maintenance, reducing unplanned downtime by ~18%.

Data Scientist

Jan 2021 – Jan 2023

Swarovski, Zurich

  • Deployed an autoencoder-based anomaly detection system to flag potentially fraudulent or unusual transactions; ~66% of flagged cases appeared in the top 100, presented via Tableau to legal teams.
  • Directed the development of a CLTV+ model combining explicit spend with inferred engagement metrics, used to guide marketing and sales resource allocation across customer segments.
  • Created predictive models for order returns and applied text analytics to detect quality signals, contributing to an ~8% reduction in return rates.
  • Supervised generation of global store-level sales forecasts for over 2,800 locations, tuning per channel and improving accuracy by ~12% on average relative to legacy Anaplan benchmarks.
  • Implemented a product-ranking optimization (PLP rank) for e-commerce using ML, driving a ~5% lift in organic conversions by surfacing more relevant items.

Senior Data Science Consultant

Jun 2018 – Oct 2020

Simon-Kucher & Partners, London & Paris

  • Led data science projects across marketing, pricing, and sales domains, managing 1–2 consultants per engagement and driving measurable client ROI and revenue growth.
  • Designed and implemented a dynamic pricing tool to forecast revenue, recommend optimal prices, and simulate occupancy for a major vacation rental platform, improving pricing accuracy by ~12–15%.
  • Devised price elasticity models for a leading French e-commerce retailer, optimizing promotions, margins, and pricing decisions.
  • Conducted segmentation and behavioral analyses for a large US fast-food chain operating in France (~570 outlets), refining targeting strategies and lifting campaign conversion through data insights.

Business Analyst Intern

Jan 2018 - Jun 2018

Amazon, Luxembourg

  • Managed ETL workflows in Redshift, refactoring legacy SQL pipelines to simplify logic and cut execution time by ~10 minutes per run, while maintaining robust data transformations for Amazon Prime.
  • Built Tableau dashboards used by ~12,000 colleagues across European fulfillment centers.

Associate Consultant

Sep 2017 – Dec 2017

Simon-Kucher & Partners, Bonn

  • Rolled out a semi-supervised mortgage recommendation model with clustering-based lead scoring, improving A/B test conversion to 15% versus 3% from standard underwriting.
  • Researched MiFID II and GDPR impacts on banking operations and advised clients on compliance, aligning growth initiatives with regulatory constraints.

Advisory, Data & Analytics Intern

Jun 2017 – Sep 2017

KPMG, Munich

  • Developed demand forecasting models using client sales data and internally collected weather features (ML + ARIMA), achieving ~12–15% MAPE and aligning KPIs with demand trends.
  • Launched an image recognition prototype in Keras and shared the results at an internal innovation event with more than 100 participants.

Education

MSc in Computational Biology

Weill Cornell Medicine, New York

Sep 2024 – Feb 2026

MSc in Business Analytics

Imperial College London

Sep 2016 – Sep 2017

BSc in Computer Science with Management

King's College London

Sep 2013 – Aug 2016

Research & Activities

Graduate Research Assistant

Nadeem Lab, Memorial Sloan Kettering

May 2025 – Present

Drove development of the DP4ALL platform to stitch whole-slide images from smartphone or microscope inputs, enabling cloud-based pathology visualization and seamless sharing.

Graduate Research Assistant

Laughney Lab, Memorial Sloan Kettering

Nov 2024 – Present

Developed Visium HD spatial transcriptomics pipeline to analyze 16 bladder cancer samples, performing cell type deconvolution to quantify tumor-stromal architecture and invasion patterns.

Investigated tumor-muscle microenvironment interactions revealing how smooth muscle cells could actively promote cancer progression through high-resolution spatial boundary analysis.

Head of Talent Development

Imperial College Data Science Society

Sep 2016 - Aug 2017

Conceptualized and delivered a comprehensive Data Science training program for over 200 students at Imperial and UCL.

Recruited and managed a team of 10 students on a churn prediction project with Expedia Group.

Skills & Languages

Languages

German (Native) Chinese (Native) French (B1)

Programming & Analytics

Python TensorFlow PyTorch scikit-learn R SQL

Data & Cloud Platforms

Azure Databricks GCP BigQuery AWS Redshift Spark Presto

Visualization & BI

Tableau Power BI R Shiny

Get In Touch

I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.