GM - Transformation & Automation Job at Vodafone (Pune)

Test Portfolio Manager

Working in tech at Australia Post is where innovation and problem solving meets ...

Location

Australia , Richmond

Salary:

Not provided

Australia Post

Expiration Date

Until further notice

Requirements

Background managing testing across multiple programs or portfolios within a large scale complex organisation
Experience leading Quality Analysts, Quality Architects and Quality Engineers
Strong experience in Agile, SDLC, Testing tools, Automation Frameworks, CI/CD pipelines Release Management, DevOps, and modern quality engineering practices
Experience implementing test automation and driving testing transformation initiatives
Proven ability to manage vendors, a distributed team, permanent and contractor resources
Extensive experience 10+ years in software testings with a focus on test management
Understanding of portfolio/program delivery models and also of risk, compliance, and quality assurance frameworks

Job Responsibility

Define and execute the portfolio testing strategy, ensuring alignment to Enterprise Services delivery priorities and standards
Provide governance and oversight of all testing activities across the portfolio
Ensure consistent adoption of test frameworks, tools, and methodologies (e.g., Agile, DevOps, automation-first approaches)
Drive standardisation and continuous improvement of testing practices across programs
Oversee the end-to-end testing lifecycle across multiple programs, including planning, execution and reporting
Ensure testing activities are aligned to delivery roadmaps, funding, and sequencing decisions
Manage interdependencies across programs and ensure integrated testing across platforms and domains
Provide assurance that releases meet quality, risk, and performance expectations
Partner with Head of Delivery, Portfolio Delivery Managers, Engineering, Product, and Architecture teams, Transformation Partner Testing Services, GM Corporate & Core Technology
Act as the primary point of contact for testing at portfolio level

What we offer

Flexible and hybrid working arrangements, like the opportunity to work from home two days per week
Opportunities for growth and development through formal programs or mentorship
Exclusive team member discounts and offers for more cash in your pocket, evolving policies for flexible working, leave types and access to health and wellbeing resources

Fulltime

GM - SCM Global Process Owner Source to Contract

We are seeking a highly experienced Global Source to Pay Process Lead who will d...

Location

India , Ahmedabad

Salary:

Not provided

Vodafone

Expiration Date

Until further notice

Requirements

Extensive experience in end-to-end Source to Pay process design, governance and transformation within complex global environments
Proven capability in leading large-scale transformation programmes across multiple markets with clear business impact
Strong stakeholder engagement and communication skills, with the ability to influence across senior leadership and matrix structures
Experience in defining KPIs, managing performance, strengthening controls and ensuring policy compliance
Knowledge of automation, AI/GenAI, analytics and enterprise systems architecture, with the ability to translate innovation into practical outcomes
Demonstrated ability to lead diverse, geographically distributed teams and deliver through collaboration
Skilled in navigating ambiguity, adapting strategies based on evolving business needs and data insights
Background in supply chain, procurement or shared services with a focus on operational excellence and continuous improvement

Job Responsibility

Lead the global Source to Pay strategy, vision and target operating model, driving harmonisation, optimisation, centralisation and digitisation
Own the development and delivery of a multi-year transformation roadmap aligned to business priorities and measurable outcomes
Define and govern global policies, process standards, controls and KPIs, ensuring continuous performance improvement and compliance
Act as a central leadership point for Source to Pay governance, collaborating with markets, shared services, finance, procurement, technology teams and external partners
Lead cross-functional transformation programmes, ensuring seamless implementation of new processes and operating models while maintaining business continuity
Drive adoption of automation, AI/GenAI, analytics and workflow simplification to enable efficient, insight-driven and increasingly touchless operations
Strengthen supplier collaboration, transparency and decision-making through data-led insights
Build and sustain strong stakeholder relationships to ensure alignment, issue resolution and consistent adoption of global standards

What we offer

Opportunity to lead a global, high-impact transformation agenda within a large-scale shared services environment
Exposure to senior stakeholders, cross-functional leadership and strategic decision-making forums
Ability to shape future-ready operating models and influence enterprise-wide process innovation
Engagement in cutting-edge digital initiatives including automation, AI and analytics
A collaborative and inclusive environment supporting professional growth and leadership development

Fulltime

Senior Software Engineer - AI Engineering and Productivity

The Role The AI Engineering and Productivity team in the Global Planning, Desig...

Location

United States , Austin; Warren

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, OR equivalent experience
6+ years of experience delivering enterprise or full stack software solutions using Java / JEE, Python , and preferably Angular
3+ years of experience working with complex SQL queries, functions, and stored procedures, including performance tuning and optimization against large datasets
Experience building or supporting data pipelines , ETL/ELT processes, or datacentric applications on distributed or cloud platforms (e.g., Databricks, Spark , or similar)
3+ years of experience with Kubernetes/Docker, Quarkus , and cloud platforms such as Azure, AWS , or GCP
Experience working in Agile/SCRUM development methodologies, including backlog refinement, sprint planning, and incremental delivery
Hands on experience with modern DevOps practices such as Git/GitHub, code reviews, automated builds, automated testing, and CI/CD pipelines (e.g., GitHub Actions)
Willingness and demonstrated ability to learn and apply AI concepts , including working with data and APIs that support AI/ML and LLM based solutions
Strong problem solving skills with the ability to break down complex technical and data challenges into clear, actionable steps and deliver high quality solutions
Excellent written and verbal communication skills with the ability to collaborate with both technical and nontechnical stakeholders

Job Responsibility

Design, develop, and maintain data driven and AI-enabled applications and services that support Product Development engineering teams
Write high-quality, performant SQL (queries, functions, stored procedures) for complex data transformations and modeling across enterprise data platforms (e.g., SQL Server, Oracle, PostgreSQL)
Build and optimize data pipelines and workflows in Databricks (DBX) and related tools to support batch and near realtime data processing
Develop backend services and APIs in Java and/or Python that integrate data, business rules, and user workflows into robust, reusable components
Develop enterprise grade applications using Kubernetes/Docker, Quarkus, Java, Angular, PostgreSQL, and other GM approved tools
Partner with data science and AI teams to productionize AI/ML and LLM based solutions, including feature pipelines, inference integrations, monitoring, and continuous improvement
Proactively identify and remediate issues related to code quality, patterns, performance, security, and data correctness, using code quality analysis tools and remediation techniques
Lead or contribute to solution design, including architecture, patterns, and technology choices aligned with GM standards and Statement of Technical Direction
Apply and champion software engineering best practices, including code reviews, automated testing, branching strategies, CI/CD pipelines (e.g., GitHub Actions), observability, and secure coding practices
Collaborate with cross-functional teams (product owners, data engineers, architects, business stakeholders) to refine requirements, define acceptance criteria, and deliver incremental value in an Agile/SCRUM environment

What we offer

Relocation benefits

Fulltime

Cadillac Sr. Reporting Analyst

The Global Ops Coe in Manila is a developing team about world class delivery, cu...

Location

Philippines , Taguig City

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree in a Data Science, Statistics, Computer Science, Mathematics, Economics, or Computer Science preferred (master's degree is a plus)
5-8 Years in Data Analytics / Data Science or related field
Working knowledge of statistical and machine learning techniques such as regression, time series forecasting, clustering, optimization, etc.
Professional experience using data science techniques to improve business results
Technical proficiency using Python and other analytical programming languages
Strong SQL and Big Data skills and proficiency in data warehouse environments such as Databricks
Highly proficient in oral and written communication skills
Background on emerging technological advancements such as AI
Data Visualization - Proficiency in Microsoft Power BI/Tableau – building dashboards, data models, and DAX measures.
Data Modeling & Integration- Experience designing data models, relationships, hierarchies, and calculated measures. Knowledge of Dataflows, Azure Synapse, or Dataverse integration (for GM’s enterprise systems) a plus.

Job Responsibility

Data Science: run Machine Learning models and maintain dashboards. The ML model helps inform Cadillac’s production and incentive decisions and the dashboards provide our HQ and field teams with actionable tools and insights for use by senior leadership or in dealer consultations
Data Modeling & Cleansing: Create consistent, validated data models for tracking operational KPIs, and customer metrics and program forecasting.
Dashboard Development: Design interactive Power BI dashboards for operational tracking/metrics, and leadership executive summary.
Advanced Analytics: Conduct trend, predictive, and segmentation analysis (e.g., which services drive subscription renewals or regional adoption).
Collaborate closely with partners across Cadillac Sales Ops, Marketing, Finance, the Cadillac Field team, and GM IT to achieve shared objectives
Solve complex problems and present expert advice to leadership in a clear and thoughtful way with a focus on actionable solutions that can be understood by a non-technical audience
Leverage state-of-the art data science and predictive statistical methodologies to enhance retail performance
Enabling scenario planning (what-if analysis): e.g., what if rollout accelerates to X number of vans
what is cost/benefit per region
what subscriber conversion assumptions make the business case viable.

Fulltime

Gbs Finance Site Lead

Work Arrangement : This role is categorized as hybrid on mid-shift, with PH–EST ...

Location

Philippines , Taguig City

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Extensive progressive leadership experience in finance, accounting, shared services, GBS, or large-scale operational finance environments
Demonstrated success leading leaders and building high-performing organizations in complex, matrixed, global environments
Proven experience shaping strategy and delivering measurable operational and transformation outcomes across multi-process finance organizations
Strong track record of leading large-scale finance modernization efforts involving process redesign, automation, ERP enablement, analytics, and governance improvements
Demonstrated ability to influence senior leaders and navigate complex stakeholder environments involving competing priorities, ambiguity, and organizational change
Bachelor’s degree in Finance, Accounting, Business, or a related field
CPA or equivalent professional qualification required

Job Responsibility

Own the Manila GBS Finance business area and provide strategic and operational leadership across multiple finance process domains, stakeholder groups, and regions
Collaborate with GBS Finance executive leadership to shape long-term strategy, operating priorities, and business objectives for the Manila organization
Translate strategic direction into actionable operating plans, resource priorities, governance routines, and measurable performance outcomes
Lead a team of teams through subordinate managers, ensuring alignment, accountability, and integrated execution across the organization
Strengthen Manila’s role as a strategic global finance hub by aligning site capabilities with enterprise needs, future operating model direction, and business growth priorities
Own delivery of critical service, productivity, quality, and control outcomes for Manila across in-scope finance operations
Establish and continuously elevate KPIs, service levels, governance mechanisms, and escalation routines to ensure reliable, high-quality, and scalable delivery
Drive standardization, simplification, and disciplined execution across finance processes to improve cost-to-serve, responsiveness, and business value
Ensure delivery performance across global stakeholders, regions, and time zones while balancing customer experience, operational rigor, and capacity optimization
Set the transformation agenda for Manila in support of Future of Finance priorities, with accountability for modernizing processes, roles, and operating models

Fulltime

Cost Engineer – Data Analytics

The Program and Purchase Cost Optimization (PPCO) team at General Motors is seek...

Location

United States , Warren

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Ability to translate ambiguous business questions into well-defined analytical and data engineering problems, and communicate findings and recommendations in a clear, structured manner to technical and non-technical stakeholders
Bachelor’s degree in computer science, engineering, statistics, mathematics, physics, or a related quantitative field (advanced degree preferred)
5+ years in data analytics (could be data science, research, or machine learning)
Python proficiency (e.g., pandas, NumPy, scikit-learn, PySpark)
SQL proficiency
Experience with Databricks, Spark, and/or other cloud-based data platforms for large-scale data processing
Experience designing and implementing ETL/ELT pipelines that integrate data from multiple transactional and analytical systems
Strong skills in EDA to understand data quality, structure, and relationship
Practical experience developing predictive models and machine learning (regression methods, Clustering and segmentation, random forests, gradient boosting)
Solid problem-solving skills and the ability to convert business questions into data and modeling problems with clear hypotheses and success criteria

Job Responsibility

Design and maintain data models and curated datasets (relational schemas, dimensional models, and feature characterizations) that support PPCO analytics and efficient downstream consumption for reporting in tools such as Power BI (while not being primarily responsible for dashboard design)
Query, integrate, and engineer data from multiple enterprise systems and relational databases, and design, build, and operate robust ETL/ELT pipelines (e.g., Databricks/Spark) to produce unified, analysis-ready datasets with appropriate data quality checks, validation, and monitoring
Perform in-depth EDA on large, heterogeneous datasets, engineer derived features (characterizations, aggregations, encodings), and understand data distributions, identify anomalies, and uncover data quality risks and insight to address by the business team
Develop and validate predictive machine learning models and descriptive models (regression, clustering, decision trees, random forests, gradient boosting, time-series/panel models), utilizing existing data to predict product attributes (geometries, cost, economic indicators) from known input parameters and historical patterns
Enable system integration across the GM ecosystem by designing the data pipelines, workflow automation and data transformation to take data from one system and turning it into a consumable format for the destination system
Automate and optimize existing cost engineering workflows by building scalable, Python-based data and analytics tools
Work across functional boundaries, including Engineering, Program Management, R&D, Finance, and Purchasing, to understand data sources, business logic, and use case

Fulltime

Dealer Audit Risk Assessment Lead – Sales

Dealer Audit plays a critical role in safeguarding the integrity of GM dealer op...

Location

United States , Detroit, Michigan;Warren, Michigan

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree in Business, Computer Science, Data Analytics, or a related field
5+ years of manufacturer-side dealership operations experience (e.g., GM or other OEMs), with deep, practical knowledge of dealer sales incentive, fleet and retail operations, including the ability to assess program design, identify control gaps, and quantify financial exposure
Knowledge of GM systems and dealer reporting platforms (e.g., RAD, Dealer Financials) or comparable enterprise systems
Demonstrated expert-level Excel capability, including advanced Power Query (M) for large-scale data transformation, automation, and audit production workflows
Experience with risk modeling, metric validation, calibration, and root-cause analysis
Exceptional ability to synthesize complex, imperfect data into clear, audience-specific summaries for auditors, managers, and senior leadership
Ability to operate at high speed in a production audit environment, managing multiple concurrent workstreams with strict delivery timelines
Demonstrated ability to rapidly switch between technical execution

Job Responsibility

Own the design, refinement, and governance of Dealer Audit’s quantitative risk-scoring and monitoring framework, integrating multiple data sources to prioritize dealers and programs for audit coverage
Serve as the functional analytics and AI leader for Dealer Audit, setting the vision and roadmap for data, dashboards, and advanced analytics (including AI) that enable scalable, technology-enabled audit execution
Act as product owner for key Dealer Audit analytics assets (e.g., Audit Results and QAR dashboards, risk dashboards), ensuring they meet the needs of leadership and auditors
Lead advanced data analytics to develop the annual Dealer Audit Risk Assessment, global audit plan, and Continuous Business Monitoring
Hands on ownership of risk logic from data ingestion through audit selection and execution, not limited to analytics support or dashboard consumption
Identify and evaluate key risk drivers across dealer operations to ensure audit coverage is focused on the highest-impact risks
Assess and enhance risk-model effectiveness through audit outcome analysis, root-cause analysis, and validation of risk indicators
Partner with GM IT and analytics teams to refine, calibrate, and expand risk metrics, with a focus on preventative and pre-validation initiatives
Support additional projects and strategic initiatives as assigned
Champion the adoption of data analytics and AI within Dealer Audit, including coaching auditors, representing the service line in GMAS data/AI initiatives, and partnering with training teams to build capabilities

Fulltime

Dealer Audit Risk Assessment Lead - Warranty

Dealer Audit plays a critical role in safeguarding the integrity of GM dealer op...

Location

United States , Detroit, Michigan; Warren, Michigan

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree in Business, Computer Science, Data Analytics, or a related field
5+ years of manufacturer‑side dealership operations experience (e.g., GM or other OEMs), with deep, practical knowledge of service and warranty operations, including the ability to assess program design, identify control gaps, and quantify financial exposure
Knowledge of GM systems and dealer reporting platforms (e.g., RAD, Dealer Financials) or comparable enterprise systems
Demonstrated expert‑level Excel capability, including advanced Power Query (M) for large‑scale data transformation, automation, and audit production workflows
Experience with risk modeling, metric validation, calibration, and root‑cause analysis
Exceptional ability to synthesize complex, imperfect data into clear, audience‑specific summaries for auditors, managers, and senior leadership
Ability to operate at high speed in a production audit environment, managing multiple concurrent workstreams with strict delivery timelines
Demonstrated ability to rapidly switch between technical execution, operational audit support, and strategic risk discussions
Proven ability to lead change and influence outcomes across IT, Data Analytics, Audit, and business program owners without formal authority
Excellent written and verbal communication skills, including executive‑level presentations

Job Responsibility

Own the design, refinement, and governance of Dealer Audit's quantitative risk‑scoring and monitoring framework, integrating multiple data sources to prioritize dealers and programs for audit coverage
Serve as the functional analytics and AI leader for Dealer Audit, setting the vision and roadmap for data, dashboards, and advanced analytics (including AI) that enable scalable, technology‑enabled audit execution
Act as product owner for key Dealer Audit analytics assets (e.g., Audit Results and QAR dashboards, risk dashboards), ensuring they meet the needs of leadership and auditors
Lead advanced data analytics to develop the annual Dealer Audit Risk Assessment, global audit plan, and Continuous Business Monitoring
Hands on ownership of risk logic from data ingestion through audit selection and execution, not limited to analytics support or dashboard consumption
Identify and evaluate key risk drivers across dealer operations to ensure audit coverage is focused on the highest‑impact risks
Assess and enhance risk‑model effectiveness through audit outcome analysis, root‑cause analysis, and validation of risk indicators
Partner with GM IT and analytics teams to refine, calibrate, and expand risk metrics, with a focus on preventative and pre‑validation initiatives
Support additional projects and strategic initiatives as assigned
Champion the adoption of data analytics and AI within Dealer Audit, including coaching auditors, representing the service line in GMAS data/AI initiatives, and partnering with training teams to build capabilities

Fulltime

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GM - Transformation & Automation

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