Based in Leamington Spa, United Kingdom

Shubham
Yadav

9+ years driving complex programmes across Tier-1 automotive OEMs — from product development at JK Tyre to requirements engineering at Jaguar Land Rover. Passionate about structured execution, stakeholder alignment, and transformational change.

PMP® Certified Jaguar Land Rover JK Tyre APQP / PPAP V-Model
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Profile

About Me

PMP®-certified Programme & Delivery Manager with 7+ years of cross-functional programme delivery across global automotive OEMs and R&D organisations. Proven track record of translating strategic briefs into structured delivery plans, with hands-on experience in BRD authoring, Agile adoption support, and JIRA-based delivery tracking. Consistent record of on-time, zero-defect OEM launches and measurable operational improvement.

At JK Tyre, I owned end-to-end programme delivery across 10+ concurrent projects and 6 major OEM launches across 5 Tier-1 brands — coordinating cross-functional teams of 10–15 from RFQ through homologation and mass-production ramp-up to ~50,000 units/month.

At JLR, I operate within a complex R&D systems engineering environment — generating and standardising requirements, facilitating stakeholder workshops, and supporting Agile adoption while influencing without formal authority.

Targeting Senior Programme / Transformation Manager roles in consulting, automotive, and financial services — where structured delivery, governance rigour, and stakeholder partnership matter.

UK Work Authorisation: Skilled Worker Visa — valid until 2028. Sponsorship required.
9+
Years of industry experience
10+
Projects managed
6
Major OEM product launches
5
OEM brands served

Case Studies

Project Portfolio

Programme Delivery
JK Tyre & Industries · Product Engineering
High-Volume
Product Delivery

Spearheaded end-to-end design validation and stakeholder orchestration for a high-volume passenger car platform — from RFQ to mass production.

50k+
Units / Month
100%
OEM Alignment
10+
Team Members
Strategic Execution
01Interpreted complex RFQs into actionable technical milestones and KPIs.
02Directed cradle-to-grave programme lifecycle: budgeting, DVP, and homologation.
03Orchestrated 10+ cross-functional members across R&D, Sales, and Production.
Value Delivered
Achieved full alignment with OEM technical and commercial performance targets.
Secured product launch approval and integrated into a ~50,000 units/month pipeline.
Implemented NPI discipline that improved delivery speed and documentation accuracy.
Programme Delivery
JK Tyre & Industries · Change Management
Change Management
& ROI Delivery

Streamlined fragmented product lines and upgraded legacy SKUs to a Strategic Target State — achieving a 50% efficiency gain with zero capital tooling investment.

50%
Efficiency Gain
Zero
Tooling Cost
4
Readiness Gates
The Problem
Fragmented legacy material lineups causing massive machine downtime and complex changeover procedures across the plant floor.
Strategic Solutioning
Unified material strategy — secured cross-functional buy-in from Production, QA, and R&D for a single-source lineup.
Legacy modernisation — upgraded old SKUs to modern performance standards without hardware changes.
Eliminated redundant changeovers, reduced machine downtime by 50%, with zero CapEx spend.
Data & Analytics
Python · EDA · Automotive
EMV Warranty
Analytics

Automotive warranty cost intelligence using the PACE framework — exploratory data analysis surfacing failure patterns and cost drivers across electric vehicle components.

PACE
Framework
Python
EDA
EV
Automotive
Scope
01Cleaned and structured synthetic warranty dataset using Python and Pandas.
02Applied PACE framework to structure the end-to-end analytical workflow.
03Identified cost drivers and failure clusters across EV component categories.
Tools Used
Python · Pandas · Matplotlib · Seaborn · Jupyter Notebook
Google Advanced Data Analytics (PACE) methodology.
Data & Analytics
Python · ML · Financial Services
Credit Risk
Model

End-to-end credit risk classification model with a live interactive Streamlit dashboard — built to demonstrate analytical and ML capability for financial services roles.

ML
Classification
Live
Streamlit App
FinServ
Domain
Scope
01Built a binary classification model to predict credit default risk from financial features.
02Deployed a live interactive Streamlit app for real-time risk scoring.
03Demonstrates end-to-end ML pipeline from data prep through model evaluation.
Key Finding
15% of the portfolio sits in Red tier carrying 41.7% default rate — 4.7× the Green tier — surfacing concentration risk to act on immediately.
Tools Used
Python · Scikit-learn · Pandas · Streamlit · GitHub
Data & Analytics
Python · XGBoost · Financial Services
FraudGuard
Transaction Fraud Intelligence

ML-powered fraud detection system built on 590,540 IEEE-CIS payment records — engineered to address the Fraud-Friction trade-off facing every retail banking operations team.

590k+
Transactions
0.896
ROC-AUC
59.6%
Fraud Caught
Scope
01EDA on 3.5% fraud rate dataset — 205 binary missingness indicators engineered as signal features.
02XGBoost with SMOTE resampling and time-based train/test split to prevent data leakage.
03Threshold tuned via F-beta (0.143 optimal) — exposing the Fraud-Friction trade-off explicitly rather than hiding it behind a single accuracy metric.
Key Finding
CNP transactions carry 11.7% fraud rate — 3.3× the portfolio average — with credit cards 2.8× riskier than debit. SHAP analysis reveals anonymised count features outperform transaction amount as fraud signals.
Tools Used
Python · XGBoost · SMOTE · SHAP · Streamlit · Plotly · Pandas

Career

Work Experience

2023 — Present Jaguar Land Rover · Gaydon, UK
Systems & Requirements Engineer
[ Requirements & Delivery Contributor — Product Engineering ]

Part of a dedicated off-cycle standardisation team within JLR's R&D environment — authoring requirements, facilitating requirements workshops, and supporting Agile adoption while influencing without formal authority across engineering, validation, and programme teams.

  • Generated and standardised engineering requirements across company-wide R&D programmes — authored and standardised technical documentation ensuring consistent interpretation across multiple programme teams and technology partners.
  • Facilitated requirements workshops with engineering and commercial stakeholders, capturing and prioritising technical constraints against programme milestones — closing a historically fragmented feedback loop between R&D and business units.
  • Supported Agile adoption within a traditional V-Model engineering team — contributed to Scrum-adjacent ceremonies and JIRA-based task tracking, improving delivery visibility while influencing without formal authority.
  • Maintained RAID logs for own workstream deliverables, developing hands-on familiarity with risk identification, dependency tracking, and escalation frameworks used across the wider programme.
  • Coordinated with senior managers across Systems Engineering to communicate requirements status, flag technical dependencies, and support programme governance activities.
V-Model Requirement Authoring Agile / Scrum JIRA RAID Logs Requirements Engineering Stakeholder Management
2016 — 2023 JK Tyre & Industries · India
Deputy Manager, Product Development
[ Engineering Programme Manager — NPD & OEM ]

7 years owning end-to-end programme delivery across a portfolio of 10+ projects, including 6 major OEM product launches across 5 Tier-1 brands — accountable for schedule, OEM client relationships, and supplier readiness from RFQ through DVP, APQP, PPAP, homologation, and mass-production ramp-up.

  • Owned end-to-end programme delivery across 10+ concurrent projects including 6 major OEM launches across 5 Tier-1 brands — accountable for schedule, OEM relationships, and supplier readiness from RFQ through DVP, APQP, PPAP, homologation, and mass-production ramp-up to ~50,000 units/month.
  • Acted as primary OEM relationship owner (SPOC) across all technical and commercial workstreams — coordinating a cross-functional team of 10–15 across R&D, Sales, Production, and QA to meet tight OEM launch windows with zero-defect delivery.
  • Secured OEM approval for a high-visibility product in the first review cycle through targeted programme optimisation and zero tooling capital investment — one of six on-time launches delivered across tenure.
  • Delivered a high-ROI change management programme consolidating fragmented legacy material lineups — leading change control, BoM alignment, and supplier readiness governance to achieve 50% improvement in production changeover efficiency with zero CapEx.
  • Built and maintained integrated programme plans mapping engineering milestones to business readiness gates; introduced structured governance forums and NPI discipline that measurably improved delivery speed and documentation accuracy.
  • Defined programme KPIs and led benefit-realisation tracking across all six launches, providing structured progress reporting to senior leadership and OEM partners throughout each lifecycle.
APQP PPAP DVP NPI / NPD Homologation RAID BoM Alignment Benefit Realisation Programme Governance

Competencies

Skills & Expertise

Programme Management
APQP / PPAP Stage-Gate RAID Management NPI / NPD CapEx Planning Risk Management Governance
Systems & Engineering
V-Model Requirements Engineering DVP DFMEA Homologation Validation Planning SPOC Traceability
Stakeholder & Delivery
Cross-functional Leadership OEM Account Management Executive Reporting Review Cadences Escalation Handling Change Management
Frameworks & Methods
Agile / Scrum Lean Thinking PMP® Framework GenAI Workflows Prompt Engineering Process Standardisation
Domain Knowledge
Automotive OEM Tyre / Rubber Technology Vehicle Systems Premium / Luxury Vehicles Product Homologation
Tools & Technology
JIRA MS Project Primavera P6 Python Tableau DOORS / Requirements Tools Microsoft Office Suite Google Workspace

Academic Background

Education

M.Tech
Design Engineering
BITS Pilani
Birla Institute of Technology & Science
B.Tech
Chemical Engineering
NIT Surat
National Institute of Technology, Surat

Professional Credentials

Certifications

PMP
Project Management Professional (PMP®)
Project Management Institute · Nov 2024 – Nov 2027
GDA
Google Advanced Data Analytics Specialization
Google · Jan 2026
P6
Primavera P6 Essential Training
LinkedIn Learning · Dec 2025
BA
Business Analysis for Project Managers
LinkedIn Learning · Nov 2025
SML
Systems Engineering with SysML
LinkedIn Learning · Nov 2025
PE
Talking to AI: Prompt Engineering for Project Managers
Project Management Institute · Nov 2024
AGL
Agile Project Management
Google · Jul 2024
GDT
Introduction to Geometric Dimensioning & Tolerancing
LinkedIn Learning · Oct 2023
RCA
Problem Solving Expert via Root Cause Analysis
Confederation of Indian Industry · Mar 2022
Six Sigma: Green Belt
LinkedIn Learning · May 2020

Thought Leadership

LinkedIn Articles

Sustainability · Circular Economy
From Fast to Last: Engineering in the Age of Circularity

A perspective on how the automotive and manufacturing industries must rethink product lifecycle — from accelerated obsolescence to circular, end-of-life-aware engineering.

Read on LinkedIn →
AI · Quality Engineering
How AI is Changing the Roles in Modern DFMEA

Exploring how artificial intelligence is reshaping Design Failure Mode & Effects Analysis — shifting the engineer's role from data-entry to strategic risk interpretation.

Read on LinkedIn →
Tyre Engineering · Vehicle Dynamics
Tyre Stiffness 101: Lateral vs. Cornering

A technical breakdown of two commonly conflated tyre properties — lateral stiffness and cornering stiffness — and why the distinction matters in vehicle handling and safety.

Read on LinkedIn →
Tyre Engineering · Consumer Insight
Driving Edge: Avoid the Top 5 Tyre Mistakes

Practical engineering insight for both vehicle owners and product managers — covering the most costly and common tyre misuse patterns that affect safety, performance, and longevity.

Read on LinkedIn →
NVH · Wheel Dynamics
Unseen Vibrations: How Your Wheels Secretly Shape Your Car's Feel

An accessible deep-dive into how wheel imbalance, runout, and vibration modes invisibly influence ride comfort, NVH characteristics, and the overall driving experience.

Read on LinkedIn →

Let's Connect

Get in Touch

Open to Programme Management, Transformation, and Consulting opportunities across the UK. Connect with me on LinkedIn.