Manish Joshi
Verified Expert in Product Management
Product Manager
Rugby, United Kingdom
Toptal member since April 12, 2021
Manish is a self-driven product and data leader with a track record of developing B2B and B2C SaaS, analytics, and AI/ML products across multiple industries, such as energy, aerospace, CPG, and financial services. He partners with cross-functional teams to create solutions that solve customer pain points and add value to the business. Manish enjoys end-to-end ownership of development and delivery, focusing on strategy, roadmap, and execution.
Project Highlights
Expertise
- Agile Product Management
- Artificial Intelligence (AI)
- Confluence
- Presentations
- Product Discovery
- Project Management
- Roadmaps
- Stakeholder Management
Work Experience
VP and Global Head of Data Engineering
Randstad Holding
- Saved a $23 million Shiseido cosmetics account from exit for Randstad by resolving all data quality issues and created a strong client relationship, resulting in additional strategic funding of $10,000.
- Architected and implemented an ETL pipeline to ingest data from GA4, Joveo, Indeed, LinkedIn, and Meta, which enabled cross-channel performance analysis, resulting in strategic decisions on marketing spend and ROI optimization.
- Streamlined the requirements gathering process and standardized the schema to reduce the time to generate business intelligence reports for clients from six weeks to one week.
- Established clear roles and responsibilities within the data engineering team to ensure alignment in priorities, clarity in accountabilities, and streamlining of ways of working to improve project delivery.
- Increased trust in data used by business intelligence dashboards by implementing automated data quality checks using Soda and standardized the ETL process so that data owners received daily alerts for proactively managing all data quality issues.
Head of Data
Westminster City Council
- Partnered with the digital leadership team and Gartner to define the digital strategy for the Smart City Operating System using their business capability framework, which helped understand the present state vs. future state requirements.
- Partnered with housing and library teams to create a “golden citizen record,” which led to the development of a Master Data Management system using DAMA and TOGAF best practices.
- Delivered air quality dashboard, which ingested data from different sensors and air quality vendors to perform ETL and analyze air quality in the London area to design a strategy that prioritized the health and wellbeing of kids and Londoners.
- Defined the council's data strategy and data governance process, identifying the resources and capabilities required to translate the Smart City vision into a roadmap and business plan.
- Scaled the data team from the ground up and hired data engineers, analysts, and scientists.
Product and Delivery Lead
Aon
- Advised engineering leadership team on governance framework and agile methodologies that were required to improve development and release cycles.
- Directed a distributed team of 16 members, which included UI/UX designers, back-end engineers, and architects. The team defined the solution architecture and delivered the SaaS platform.
- Introduced governance across 9 projects and tracked delivery methods to ensure continuous improvement in agile delivery methods. Presented monthly KPI reports to the COO.
- Improved report processing time (queuing + run time) by 50% while maintaining cloud infra costs, improvement in on-time delivery, velocity, and burndown rate.
- Led development of an event-driven, distributed analytics and rendering solution to deliver a real-time B2B SaaS analytics platform which improved UX by over 50%.
- Delivered key customer requirement of ingesting 100k msgs/hr by identifying and removing technical bottlenecks in existing data pipeline which improved data ingestion rate from 10k msgs/hr to 100k msgs/hr reducing onboarding time by over 60%.
Principal Consultant Product Manager
Toptal Clients
- Developed predictive models for each retailer of the global beverage company by optimizing return on ad spends based on factors such as pricing, seasonality, availability, etc. The company has over 100 brands, each with hundreds of products.
- Led an ML team for the company's eCommerce business, working closely with data science and engineering teams to build predictive models, resulting in a 6% uplift for Amazon and 40% for Kroger on select PepsiCo products after 8 weeks of A/B testing.
- Engaged with Amazon and Kroger teams to understand lifecycle management policies for UPCs/SKUs to improve training data quality and streamline marketing processes.
Digital Transformation Leader
General Electric
- Scaled engineering, analytics, and the data science team from the ground up to deliver digital transformation for the Industrial Steam Turbine business and developed an integrated platform. It has $35M in annual benefits to the business.
- Directed global teams to build and deliver a real-time data analytics app that performed predictive maintenance to prevent defects for over 1,000 parameters by creating data maps resulting in annual savings of $11 million.
- Exceeded business objective and delivered an integrated platform, improving operational efficiency by reducing contract execution time by about 33%, along with quality of deliverables.
- Identified opportunities and built up the team's technical capabilities to build the first AI app for the business with 86% accuracy in detecting anomalies of 3D printed parts, reducing the manual inspection time by 90% and saving $2.5 million.
- Developed an AI app to predict the scrap rate for airfoil blades based on design and manufacturing parameters validated by manufacturing teams resulting in about 19% reduction in scrap, saving about $1.5 million per contract.
- Created a centralized cost database to ensure consistency in pricing calculations, nominated key users as owners of components of cost structure, and organized training workshops on using a controlled process for maintenance and updates.
- Managed the migration of a SaaS-based PLM application that improved operational efficiency by $3 million annually across four locations by finalizing requirements and organizing testing and training sessions to ensure a seamless transition.
- Achieved a ten times increase in sales activities from 63 to 600+ budgetary bids per year; reduced the time to generate bid documents to less than three minutes by standardizing technical and commercial information required to create a bid document.
- Led the development of an IoT solution for the business, which included building the roadmap and identifying analytics and infrastructure requirements to perform real-time preventive maintenance to reduce forced outages and improve reliability.
- Engaged with the corporate IT team to define the governance mechanism for regular platform maintenance and updates and quality audits to ensure compliance with prescribed GE cybersecurity standards.
Product Owner
Eaton
- Created an automated process for design optimization of pressure switches and transducers, reducing design cycle time by 60%.
- Mentored engineers and interns through weekly meetings to review progress on development priorities and provided targeted feedback to improve technical and soft skills, resulting in two interns being offered permanent roles.
- Delivered high-visibility projects for customers like Boeing, BAE, and Fokker by finalizing requirements with customers, collaborating with the team to create project plans, and passing design reviews, enabling timely certification of the parts.
Tech Lead
General Electric
- Streamlined the design process by developing tools that linked different design process steps, eliminating the need for conceptual design review and reducing cycle time from over two weeks to 22 minutes, resulting in $250k savings per project.
- Developed a tool that performed design and non-design calculations for the turbine section using first principles and loss models to calculate turbine section efficiency and give design details based on input conditions.
- Performed competitive assessment to understand technological differences between GE and other OEM turbines, which helped develop a product strategy to gain a competitive advantage in the energy market.
Project Engineer
National Aerospace Laboratories
- Designed the turbine section using first principles to support the development of a turbofan engine in an indigenously designed military aircraft aimed to develop local design and manufacturing expertise of aerospace components in the country.
- Developed tools in VB to predict design and off-design performance of a turbine section using loss models, which showed good correlations with CFD calculations and increased the confidence level in the tool and reducing the design optimization cycle.
- Integrated the tool with the rest of the application to optimize the entire flow path based on input conditions and reducing design cycle time from weeks to days.
Project History
Integrated Platform Development
Led the end-to-end development of an integrated platform that all employees used daily, which helped improve internal productivity by over 33%.
Key Deliverables:
• Oversaw the end-to-end management of the platform and was the person accountable for its development.
• Created a blueprint based on the vision.
• Got buy-in from all key stakeholders, including our business leader.
• Developed a roadmap and business case for each product, including the MVPs.
• Created project plans.
• Secured resources to ensure products were delivered on time and were in line with customer expectations.
• Managed an annual budget of $1.5 million and worked with project teams of 12-15 people across six global locations.
• Followed the Agile philosophy and held biweekly sprint meetings to finalize user stories and daily stand-ups to discuss progress and troubleshoot issues.
My team included 15 members, including product owners and software engineers.
Machine Learning Application
Showcased AI benefits by identifying and developing the team's technical capabilities to develop the first AI app for the business; an 86% accuracy in detecting anomalies of 3D printed parts resulted in over 90% reduction in manual inspection time.
• Engaged with manufacturing to identify the need to improve the productivity of 3D printed components by using supervised machine learning techniques.
• Finalized development plans for the team, undertook formal training and certification in machine learning courses to develop knowledge. The team comprised of two data science engineers responsible for training the model, two software engineers to integrate with the platform, and technical owners from manufacturing to support with data collection.
• Created a program plan and business case highlighting value and timelines for MVP and prototype development to ensure outcomes align with expectations.
• Collaborated with manufacturing engineers to create a valid data set on which the model can be trained.
• Used image augmentation techniques to improve the performance, which resulted in a model with 86% accuracy in detecting defective images.
Cost Database
Created a database to ensure consistency in cost and price calculations across the business and nominated key users for cost structure components; organized training to emphasize the use of a controlled process for database maintenance and updates.
• Engaged with sales, tendering, sourcing, project management, and engineering to create a cost database.
• Organized and led a brainstorming session to understand the cost data required and used by each team.
• Worked with our software development team to develop a database to include all components of the cost and price structure along with approval mechanisms for change management to prevent random updates to the database.
• Led a project team of about 14 members and delivered the prototype in six months.
Education
Master of Business Administration (MBA) in Business Administration
Bayes (Cass) Business School - London
Master's Degree in Thermal Power
Cranfield University - Cranfield, England
Certifications
Managing Successful Programmes
Axelos
PRINCE2 Agile Practitioner Certification
Axelos
PRINCE2 Practitioner Certification
Axelos
Lean Six Sigma
General Electric
Skills
Tools
Confluence, Jira, Microsoft Project, Apache Airflow, ETL
Paradigms
Scrum, Six Sigma, Agile Product Management, Agile Project Management, Agile, Kanban, Data Product Management, Azure DevOps
Industry Expertise
Energy, Oil & Gas, Aviation, Consumer Products, Aerospace & Defense
Platforms
Azure, Google Cloud Platform (GCP)
Other
Business Management, Program Management, Project Management, Lean, Python 3, Leadership, Stakeholder Management, Optimization, Software Development Lifecycle (SDLC), Negotiation, Stakeholder Engagement, Product Management, Product Ownership, Cross-functional Team Leadership, Scikit-learn, SQL, PostgreSQL, Excel VBA, Digital Product Management, Digital Product Development, Product Strategy, Product Roadmaps, Regulated Industries, Lean Manufacturing, Process Improvement, Process Mapping, Internet of Things (IoT), Industrial Internet of Things (IIoT), Vendor Management, Dashboards, Reporting, Portals, Manufacturing, Power Generation, Communication, Information Technology, Open Source, Software Engineering, Software, Roadmaps, Product Discovery, Presentations, ROI, User Personas, Big Data Architecture, Market Research, Research, Business Analysis, Product Owner, Data Analysis, Data Product Manager, Data Products, Automation, AI Consulting, Machine Learning, Amazon Web Services (AWS), Artificial Intelligence (AI), Artificial Intelligence Product Manager, Data Science Product Manager, SaaS, SaaS Product Management, eCommerce, Call Centers, Vendor Selection, Telemetry, User Research, Supply Chain, Marketing Technology (MarTech), Advertising Technology (Adtech), TensorFlow, Keras, Data Science, Data Analytics, Product Development, Team Building, Design Collaboration, Web UX, User Stories, Technical Product Management, Natural Language Processing (NLP), Security, Order Management, Agile DevOps, Waterfall Delivery, Digital Transformation, Strategy, Innovation, Entrepreneurship, Kubernetes, Apache Kafka, Apache Spark, Data-driven Dashboards, Risk Assessment, Agile Delivery, Product Delivery, Data Strategy, Digital Strategy, Generative Pre-trained Transformers (GPT), Big Data, Data Engineering, Python, Finance
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