Raghav Dave CV

Professional Summary

Experienced Lead Data Scientist with a strong background in developing and implementing end-to-end machine learning solutions, MLOps practices, and driving innovation in the automotive and insurance industries. Proven track record in technical leadership, cross-functional collaboration, and delivering impactful data-driven solutions. Only data science relevant experiences are listed below.

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Senior Data Scientist @ Toyota Connected Europe

March 2022 → present

Led end-to-end development of EcoScore solution (scoring and coaching drivers on energy efficiency) for eco-fleet (fleet management for Paris Olympics), incorporating innovative feature engineering and MLOps practices.
The solution led to 500k+ of total trips across 2.5k+ vehicles being scored on energy efficiency and each trip explained on what behavioural change would impact energy efficiency the most → ultimately helping achieve the goal of <40g/km emissions.
Developed Multimodal ML solution to estimate EV Battery State of Health using contextual data including driving patterns, charging patterns, vehicle and weather conditions to provide actionable insights for a variety of uses cases, including prolonging battery life, residual value and fleet charing solutions.
Spearheaded refactoring of Driving Analytics (an analytics codebase written in python that generates trip insights), transforming a big spaghetti codebase into modular and robust codebase, whilst also improving accuracy, efficiency, latency, and maintainability
Led Driving Analytics project, making strategic decisions in product roadmap
Established and implemented MLOps templates and practices covering entire model SDLC, including data & artifact version control, experiment tracking, deployment, model quality, data quality & drift, bias and explainability monitoring for customer-facing projects; whilst overcoming budget and resource constraints using open-sources stack.
Led the initiative of Data Dictionary : an internal data catalogue enhancing company-wide understanding of the available data, and educating the importance of making data documentation across the company.
Served as primary point of contact for several data science projects, handling development, L3 support, and improvements.
Conducted several internal discovery, brainstorming and technical feasibility assessments identifying and developing POCs for potential business opportunities

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Senior Data Scientist @ Kainos

October 2020 → March 2022

Kainos AI Practice (Internal IP Accelerators Development, and Workshops)

Held several Azure Machine Learning workshops, with a wide audience
Contributed towards developing internal IP accelerators for MLOps on Azure and AWS.

**FBD Insurance (Client Projects on Azure Machine Learning)**

Involved in requirements gathering, led the discovery sessions to engage with key departmental heads to capture the processes and business challenges, and prioritise analytics opportunities, coaching and handover sessions.
Developed and deployed Singularity Model, an AI based client matching solution to match and group identical quotes coming from the same customers, running as a service on Azure Cloud.
Developed and deployed a Propensity Model to predict likelihood of conversion with high time-dependency features, along with the complete MLOps pipeline to automate regular retraining and re-deployment of the Model using Azure Machine Learning Pipelines and Azure DevOps.
The project outcome was significantly increasing the CRM team’s efficiency by directing their focus and energy down from 300 quotes to top 5-10 customers to callback to on an hourly basis.

**Home Office (Client Project – Cloud Migration)**

Worked closely with Data Engineers, Software Engineers and Technical Architects to update analytics codebase for migration from on-premises database & services to AWS Redshift.

**National Crime Agency (Client Project - Community Detection)**

Leveraged Neo4j graph database and advanced graph analysis algorithms to develop a Community Detection solution, enhancing the agency's ability to identify and map complex criminal networks. </aside>

Senior Data Scientist @ Kavida.ai

March 2020 → August 2022 (Freelance)

Led data science stream for AI-based supply chain resilience platform; helping build the internal data science capability
Developed and deployed Bankruptcy Classification Engine to predict supplier bankruptcy
Developed and deployed Threat Identification Model (Supply Chain) and profiling engine using NLP and AWS Lambda
Established MLOps roadmap, templates and practices for continuous retraining and deployment on AWS using Sagemaker and MLFlow </aside>

Data Scientist @ Atkins (SNS Lavalin)

September 2019 → October 2020

Led predictive modelling of weather-based Weather Based Asset Failure Prediction Model for Network Rail, leading to predictive maintenance, minimising costs, delays and improving customer journeys
Developed ensembled classification solution for asset failure prediction, deployed as a geo-spatial dashboard </aside>

Contact

Phone: 07970654781

Email: [email protected]

Address: London, UK

Web CV: bit.ly/raghav-dave

LinkedIn: https://www.linkedin.com/in/daveraghav/

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MEng in Aerospace Engineering

Brunel University London, July 2016

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Skills

Cloud platforms: AWS SageMaker, Azure Machine Learning,
Data Science: Supervised and Unsupervised Learning including clustering, classification, regression, time-series, graph / network analysis & data science, NLP, deep learning
ML Frameworks: sklearn, xgboost, catboost, tensorflow, neo4j
Tools: Power BI, Git, JIRA, Jenkins, Confluence, DVC, VSC, MLFlow, S3, Azure Blob
Languages: Python, SQL, Bash
Databases: Postgres, MongoDB, Athena, AWS Redshift
Consulting: Presentations, Knowledge Transfer, Requirements Gathering, Consulting Sessions, Discovery Sessions.
Leadership and Coaching: Managing a team of up to 5 to lead technical projects, mentor junior members </aside>

Certifications

TensorFlow Developer Certification
AWS Certified Machine Learning - Specialty
Azure Data Scientist Associate
Azure AI Engineer Associate </aside>

Key Achievements

HackTrain VI Performance Challenge winner for developing tool to predict asset failures based on historic data.
TDS Blogger
Hosted Pie and AI Webinars </aside>

Learn More About Me

Projects

Tech Stack

Skills

Employers and Clients

Blogs

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