16 Critical Thinking jobs in India
Product Owner – Intelligent Decision Making
Posted today
Job Viewed
Job Description
India is among the top ten priority markets for General Mills, and hosts our Global Shared Services Centre. This is the Global Shared Services arm of General Mills Inc., which supports its operations worldwide. With over 1,300 employees in Mumbai, the center has capabilities in the areas of Supply Chain, Finance, HR, Digital and Technology, Sales Capabilities, Consumer Insights, ITQ (R&D & Quality), and Enterprise Business Services. Learning and capacity-building is a key ingredient of our success.
Position Title
Product Owner, Intelligent Decision Making & Operations
Function/Group
GIC Supply Chain – Global Planning Hub
Location
Mumbai
Shift Timing
1:30 pm – 10:30 pm
Role Reports to
Capability Lead – Strategic Initiative
Remote/Hybrid/in-Office
Hybrid
About General Mills
We make food the world loves: 100 brands. In 100 countries. Across six continents.
With iconic brands like Cheerios, Pillsbury, Betty Crocker, Nature Valley, and Häagen-Dazs, we've been serving up food the world loves for 155 years (and counting). Each of our brands has a unique story to tell.
How we make our food is as important as the food we make. Our values are baked into our legacy and continue to accelerate
us into the future as an innovative force for good. General Mills was founded in 1866 when Cadwallader Washburn boldly bought the largest flour mill west of the Mississippi. That pioneering spirit lives on today through our leadership team who upholds a vision of relentless innovation while being a force for good. For more details check out
General Mills India Center (GIC) is our global capability center in Mumbai that works as an extension of our global organization delivering business value, service excellence and growth, while standing for good for our planet and people.
With our team of 1800+ professionals, we deliver superior value across the areas of Supply chain (SC) , Digital & Technology (D&T) Innovation, Technology & Quality (ITQ), Consumer and Market Intelligence (CMI), Sales Strategy & Intelligence (SSI) , Global Shared Services (GSS) , Finance Shared Services (FSS) and Human Resources Shared Services (HRSS).For more details check out
We advocate for advancing equity and inclusion to create more equitable workplaces and a better tomorrow.
Job Overview
General Mills is accelerating the Digital Transformation & Intelligent Decision making for our Supply Chain. This transformation will be a key enabler for our Supply Chain and business strategies and provide a competitive advantage to our business. Our vision for Supply Chain Intelligent Decision-making & Execution is to bring together people, process, and technology with access to real-time information so that they can more quickly sense and analyze risk and opportunity and make better, more end-to-end decisions. Over time, this will enable us to automate key executional decisions. As the Product Owner - Intelligent Decision Making & Operations, you will lead the design & decision, development, and scaling of data driven, AI/ML powered solutions that enable faster and smarter supply chain decisions. You will also drive transformation of operations, identifying automation opportunities and embedding intelligence into end to end processes. The role blends product thinking, agile delivery and operational insights.We are seeking a high energy and passionate individual who fundamentally believes that digital products are mission critical for GMI. The ideal candidate thrives in an entrepreneurial and fast-paced setting, challenges the status quo, and enjoys finding efficient solutions and out-of-the box ideas. They seek out and embrace change. To be successful in this role, you must be able to quickly learn how different functions operate and be able to navigate a cross-functional matrix at multiple levels.
Function Overview
The GIC Supply Chain team manages end-to-end operations, encompassing planning, sourcing, manufacturing, logistics, and analytics. They strategically plan to meet ma rket demands, optimize sourcing, ensure efficient production, and oversee the seamless movement of goods from production to delivery. The team employs advanced analytics throughout these processes, fostering adaptability and operational excellence. This collaborative approach ensures a well-coordinated supply chain that aligns with both organizational goals and dynamic market conditions.
For more details about the Function please visit this Link
Key Accountabilities
Intelligent Decision-making
- Ideate & support the product vision & roadmap for intelligent decision-support tools across supply chain domain
- Work closely with digital/ data science teams to design, test and iterate POCs and MVPs with measurable business outcomes
- Partner with global and local team to drive user adoption and training.
- Establish Pod standards, metrics, tracking, ways of working, and support mechanics. Primary face of the Pod to the tool SMEs.
- Discover, define & refine business requirements continuously. Navigate tradeoffs.
- Set and deliver quarterly OKRs (Objectives & Key Results - clearly defined quarterly Pod goals).
- Maintain and track business value of products with SMEs .
- Define and analyze metrics that inform impact on customer experience and business outcomes .
- Support SMEs to maintain adoption rates with end users.
- Work with Tech Lead and Agile Coach to continuously improve POD maturity .
Intelligent Operations
- Identify manual, repetitive and intensive processes across supply chain operations (including GIC)
- Conduct process diagnostics with local teams to prioritize automation or augmentation opportunities (eg., RPA, intelligent workflows etc)
- Collaborate with automation & digital team to deliver scalable solutions & measure ROI
- Champions the culture of intelligent operations
- Monitor implementation impacts: cycle time reduction, effort savings and SLA enhancement
Required Skills/Experience
- Strong leadership skills, including the ability to drive change
- Strong influence skills and ability to influence across functions and business strategies
- Excellent communication and collaboration skills
- Project management experience with Agile framework
- Strong organizational and people development skills
- Able to lead and direct cross functional team members
- Self-managing, results oriented and capable of leading multiple initiatives simultaneously
- Able to enter uncertain/ambiguous situations, assess opportunities, identify stakeholders, and bring direction to a project, take action, and deliver results
- Strong analytical thinking and creative problem solving
- Ability to work in global multi-cultural teams (global organizations/MNCs)
- Demonstrated high level of learning & cultural agility.
Minimum Qualifications
- Bachelor's or Master's Degree in Engineering, Supply Chain.
- 12+ years of related experience mainly in Supply chain, Business and Digital transformation projects, Product ownership
- Experience of Intelligent Execution/ decision making projects
Company Overview
We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one other and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what's next.
Data Driven Decision Making Specialist
Posted today
Job Viewed
Job Description
We are seeking a skilled Implementation and Analytics Specialist to join our team. The ideal candidate will have a strong background in digital analytics and implementation, with a proven track record of delivering high-quality results.
The key responsibilities of this role include:
- Supporting day-to-day analytics implementation tasks
- Collaborating with product teams during new launches to ensure data readiness
- Working closely with marketing teams to enable accurate tracking for campaigns
- Performing rigorous QA of tracking implementations using GA4 and Segment
- Supporting reporting needs through dashboard configuration and ad hoc data pulls
- Assisting in identifying data gaps and helping surface actionable insights
- Ensuring alignment of tagging strategy across stakeholders and platforms
Required skills include:
- Proven expertise in GA4 implementation
- Working knowledge of Segment.io
- Strong understanding of marketing measurement and user behavior analytics
- High attention to detail
- Ability to collaborate effectively with external product and marketing teams
- Strong communication and documentation skills
The ideal candidate will have a minimum 5 years of experience in digital analytics or implementation roles. They must have excellent QA habits and a detail-oriented mindset. Digital tag management platforms such as GTM, Adobe Launch are also a plus.
This role plays a key part in enabling data-driven decision-making through robust tagging, QA, and measurement practices. The specialist will work closely with cross-functional teams including marketing, product, and client-side stakeholders. They will configure dashboards, conduct ad-hoc analysis, and maintain documentation and best practices for implementation and tracking governance.
Data-Driven Decision Making Specialist
Posted today
Job Viewed
Job Description
The Implementation & Analytics Specialist plays a vital role in ensuring accurate analytics implementation, campaign tracking, and insightful reporting for marketing and product functions. This specialist will support data-driven decision-making through robust tagging, QA, and measurement practices.
- Supporting day-to-day analytics implementation tasks as part of ongoing business-as-usual (BAU) activities.
- Collaborating with product teams during new launches to ensure data readiness.
- Working closely with marketing teams to enable accurate tracking for campaigns.
- Performing rigorous QA of tracking implementations using Google Analytics 4 (GA4) and Segment.io.
- Supporting reporting needs through dashboard configuration and ad hoc data pulls.
- Assisting in identifying data gaps and helping surface actionable insights.
- Ensuring alignment of tagging strategy across stakeholders and platforms.
Role Requirements
Required skills and competencies include:
- Proven expertise in GA4 implementation and tag validation processes.
- Working knowledge of Segment.io for event tracking and data routing.
- Strong understanding of marketing measurement and user behavior analytics.
- High attention to detail with a structured QA mindset.
- Ability to collaborate effectively with external product and marketing teams.
- Strong communication and documentation skills.
This role requires a minimum of 5 years of experience in a digital analytics or implementation role, with direct interaction with external teams including marketing and product functions across client-side stakeholders.
Lead Visionary for Data-Driven Decision-Making
Posted today
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Job Description
Birdeye empowers businesses to attract, engage and retain customers by listening to feedback and turning it into growth opportunities. We're seeking a forward-thinking Business Insights Leader who will drive the future of data-driven decision-making across our global organization.
This is a high-impact, high-visibility role where you will own analytics, forecasting, and advanced modeling to optimize revenue growth, marketing efficiency, and pipeline strategy. You will work closely with our global leadership team aligning to US working hours and play a pivotal role in shaping how we grow worldwide.
Key Responsibilities:
Driving Business Growth Through Data-Driven Decision Making
Posted today
Job Viewed
Job Description
We're seeking a strategic Data Insights Professional to drive business growth through data-driven decision making.
This role requires a deep understanding of commercial Patient Analytics and advanced manipulation of real-world healthcare datasets.
- Lead the full lifecycle of product development from conception to market launch, leveraging analytics to uncover key trends and opportunities.
- Conduct market sizing, cohort analysis, risk stratification, and KPI modelling to inform product strategies.
- Develop automated data pipelines to improve reporting efficiency and deliver faster insights.
- Collaborate with cross-functional teams to translate analytical insights into scalable solutions that align with our platform vision.
The ideal candidate will have 5+ years of experience in data science, commercial data analytics, or advanced data interpretation.
Visiting Faculty for the Course: Data Analytics for Retail Decision-Making, MBA
Posted 2 days ago
Job Viewed
Job Description
Visiting Faculty for the MBA Technology Management Program
Position Title:
Visiting Faculty
Course:
Data Analytics for Retail Decision-Making, MBA
Location:
Yelahanka, Bangalore, Karnataka
Mode:
On Campus, no online classes
Duration:
One Term of a Trimester (extendable based on academic needs and performance)
20th October 2025 to 31st December 2025
Course Overview
The course “Data Analytics for Retail Decision-Making” is designed to equip MBA and postgraduate management students with analytical tools and data-driven approaches for solving real-world retail business problems. It focuses on developing the ability to interpret, model, and leverage data for improving decisions in areas such as customer management, pricing, inventory, promotion, and supply chain optimization.
Key thematic areas include:
- Fundamentals of data analytics in the retail context
- Retail data collection, preparation, and visualization
- Predictive modeling for sales forecasting and demand estimation
- Customer segmentation and recommendation systems
- Pricing, promotion, and assortment optimization using data analytics
- Application of AI/ML tools in retail strategy
- Ethical and privacy considerations in retail data analytics
Key Responsibilities
- Design and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applications
- Integrate business and management context into technical topics to suit MBA and postgraduate students
- Develop case studies, datasets, and simulation-based exercises
- Mentor students on AI/ML projects and practical applications
- Collaborate with TAPMI faculty on course design, assessment, and AACSB/AoL requirements
- Contribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-making
Qualifications
Essential:
- Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field
- Demonstrated expertise in AI/ML, with teaching or corporate training experience
- Proficiency in Python, R, or equivalent programming environments for machine learning
Desirable:
- Industry or research experience in retail analytics, marketing analytics, or consumer insights
- Familiarity with AI/ML applications and optimization techniques in retail contexts
- Record of applied research, consulting, or publications in analytics-driven retail strategy
Skills and Competencies
- Ability to simplify complex technical concepts for management students
- Strong communication and classroom engagement skills
- Ability to bridge theory with real-world applications
- Collaborative mindset and commitment to academic excellence
Remuneration
Compensation will be commensurate with qualifications, experience, and profile , and in line with TAPMI’s norms for visiting faculty.
Application Process
Interested candidates may send their applications to Prof. Deepak A S ( ), Analytics Area Chair, with the subject line: “Application – Visiting Faculty (Data Analytics for Retail Decision-Making)”
The application should include:
- Detailed CV (with academic, teaching, and industry experience)
- List of two professional references
Visiting Faculty for the Course: Data Analytics for Retail Decision-Making, MBA
Posted 2 days ago
Job Viewed
Job Description
Visiting Faculty for the MBA Technology Management Program
Position Title:
Visiting Faculty
Course:
Data Analytics for Retail Decision-Making, MBA
Location:
Yelahanka, Bangalore, Karnataka
Mode:
On Campus, no online classes
Duration:
One Term of a Trimester (extendable based on academic needs and performance)
20th October 2025 to 31st December 2025
Course Overview
The course "Data Analytics for Retail Decision-Making" is designed to equip MBA and postgraduate management students with analytical tools and data-driven approaches for solving real-world retail business problems. It focuses on developing the ability to interpret, model, and leverage data for improving decisions in areas such as customer management, pricing, inventory, promotion, and supply chain optimization.
Key thematic areas include:
- Fundamentals of data analytics in the retail context
- Retail data collection, preparation, and visualization
- Predictive modeling for sales forecasting and demand estimation
- Customer segmentation and recommendation systems
- Pricing, promotion, and assortment optimization using data analytics
- Application of AI/ML tools in retail strategy
- Ethical and privacy considerations in retail data analytics
Key Responsibilities
- Design and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applications
- Integrate business and management context into technical topics to suit MBA and postgraduate students
- Develop case studies, datasets, and simulation-based exercises
- Mentor students on AI/ML projects and practical applications
- Collaborate with TAPMI faculty on course design, assessment, and AACSB/AoL requirements
- Contribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-making
Qualifications
Essential:
- Master's degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field
- Demonstrated expertise in AI/ML, with teaching or corporate training experience
- Proficiency in Python, R, or equivalent programming environments for machine learning
Desirable:
- Industry or research experience in retail analytics, marketing analytics, or consumer insights
- Familiarity with AI/ML applications and optimization techniques in retail contexts
- Record of applied research, consulting, or publications in analytics-driven retail strategy
Skills and Competencies
- Ability to simplify complex technical concepts for management students
- Strong communication and classroom engagement skills
- Ability to bridge theory with real-world applications
- Collaborative mindset and commitment to academic excellence
Remuneration
Compensation will be commensurate with qualifications, experience, and profile , and in line with TAPMI's norms for visiting faculty.
Application Process
Interested candidates may send their applications to Prof. Deepak A S (), Analytics Area Chair, with the subject line: "Application - Visiting Faculty (Data Analytics for Retail Decision-Making)"
The application should include:
- Detailed CV (with academic, teaching, and industry experience)
- List of two professional references
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Visiting Faculty for the Course: Data Analytics for Retail Decision-Making, MBA
Posted 1 day ago
Job Viewed
Job Description
Position Title:
Visiting Faculty
Course:
Data Analytics for Retail Decision-Making, MBA
Location:
Yelahanka, Bangalore, Karnataka
Mode:
On Campus, no online classes
Duration:
One Term of a Trimester (extendable based on academic needs and performance)
20th October 2025 to 31st December 2025
Course Overview
The course “Data Analytics for Retail Decision-Making” is designed to equip MBA and postgraduate management students with analytical tools and data-driven approaches for solving real-world retail business problems. It focuses on developing the ability to interpret, model, and leverage data for improving decisions in areas such as customer management, pricing, inventory, promotion, and supply chain optimization.
Key thematic areas include:
- Fundamentals of data analytics in the retail context
- Retail data collection, preparation, and visualization
- Predictive modeling for sales forecasting and demand estimation
- Customer segmentation and recommendation systems
- Pricing, promotion, and assortment optimization using data analytics
- Application of AI/ML tools in retail strategy
- Ethical and privacy considerations in retail data analytics
Key Responsibilities
- Design and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applications
- Integrate business and management context into technical topics to suit MBA and postgraduate students
- Develop case studies, datasets, and simulation-based exercises
- Mentor students on AI/ML projects and practical applications
- Collaborate with TAPMI faculty on course design, assessment, and AACSB/AoL requirements
- Contribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-making
Qualifications
Essential:
- Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field
- Demonstrated expertise in AI/ML, with teaching or corporate training experience
- Proficiency in Python, R, or equivalent programming environments for machine learning
Desirable:
- Industry or research experience in retail analytics, marketing analytics, or consumer insights
- Familiarity with AI/ML applications and optimization techniques in retail contexts
- Record of applied research, consulting, or publications in analytics-driven retail strategy
Skills and Competencies
- Ability to simplify complex technical concepts for management students
- Strong communication and classroom engagement skills
- Ability to bridge theory with real-world applications
- Collaborative mindset and commitment to academic excellence
Remuneration
Compensation will be commensurate with qualifications, experience, and profile, and in line with TAPMI’s norms for visiting faculty.
Application Process
Interested candidates may send their applications to Prof. Deepak A S ( ), Analytics Area Chair, with the subject line: “Application – Visiting Faculty (Data Analytics for Retail Decision-Making)”
The application should include:
- Detailed CV (with academic, teaching, and industry experience)
- List of two professional references
Visiting Faculty for the Course: Data Analytics for Retail Decision-Making, MBA
Posted today
Job Viewed
Job Description
Visiting Faculty for the MBA Technology Management Program
Position Title:
Visiting Faculty
Course:
Data Analytics for Retail Decision-Making, MBA
Location:
Yelahanka, Bangalore, Karnataka
Mode:
On Campus, no online classes
Duration:
One Term of a Trimester (extendable based on academic needs and performance)
20th October 2025 to 31st December 2025
Course Overview
The course “Data Analytics for Retail Decision-Making” is designed to equip MBA and postgraduate management students with analytical tools and data-driven approaches for solving real-world retail business problems. It focuses on developing the ability to interpret, model, and leverage data for improving decisions in areas such as customer management, pricing, inventory, promotion, and supply chain optimization.
Key thematic areas include:
- Fundamentals of data analytics in the retail context
- Retail data collection, preparation, and visualization
- Predictive modeling for sales forecasting and demand estimation
- Customer segmentation and recommendation systems
- Pricing, promotion, and assortment optimization using data analytics
- Application of AI/ML tools in retail strategy
- Ethical and privacy considerations in retail data analytics
Key Responsibilities
- Design and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applications
- Integrate business and management context into technical topics to suit MBA and postgraduate students
- Develop case studies, datasets, and simulation-based exercises
- Mentor students on AI/ML projects and practical applications
- Collaborate with TAPMI faculty on course design, assessment, and AACSB/AoL requirements
- Contribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-making
Qualifications
Essential:
- Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field
- Demonstrated expertise in AI/ML, with teaching or corporate training experience
- Proficiency in Python, R, or equivalent programming environments for machine learning
Desirable:
- Industry or research experience in retail analytics, marketing analytics, or consumer insights
- Familiarity with AI/ML applications and optimization techniques in retail contexts
- Record of applied research, consulting, or publications in analytics-driven retail strategy
Skills and Competencies
- Ability to simplify complex technical concepts for management students
- Strong communication and classroom engagement skills
- Ability to bridge theory with real-world applications
- Collaborative mindset and commitment to academic excellence
Remuneration
Compensation will be commensurate with qualifications, experience, and profile , and in line with TAPMI’s norms for visiting faculty.
Application Process
Interested candidates may send their applications to Prof. Deepak A S ( ), Analytics Area Chair, with the subject line: “Application – Visiting Faculty (Data Analytics for Retail Decision-Making)”
The application should include:
- Detailed CV (with academic, teaching, and industry experience)
- List of two professional references
Visiting Faculty for the Course: Data Analytics for Retail Decision-Making, MBA
Posted today
Job Viewed
Job Description
Visiting Faculty for the MBA Technology Management Program
Position Title:
Visiting Faculty
Course:
Data Analytics for Retail Decision-Making, MBA
Location:
Yelahanka, Bangalore, Karnataka
Mode:
On Campus, no online classes
Duration:
One Term of a Trimester (extendable based on academic needs and performance)
20th October 2025 to 31st December 2025
Course Overview
The course “Data Analytics for Retail Decision-Making” is designed to equip MBA and postgraduate management students with analytical tools and data-driven approaches for solving real-world retail business problems. It focuses on developing the ability to interpret, model, and leverage data for improving decisions in areas such as customer management, pricing, inventory, promotion, and supply chain optimization.
Key thematic areas include:
- Fundamentals of data analytics in the retail context
- Retail data collection, preparation, and visualization
- Predictive modeling for sales forecasting and demand estimation
- Customer segmentation and recommendation systems
- Pricing, promotion, and assortment optimization using data analytics
- Application of AI/ML tools in retail strategy
- Ethical and privacy considerations in retail data analytics
Key Responsibilities
- Design and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applications
- Integrate business and management context into technical topics to suit MBA and postgraduate students
- Develop case studies, datasets, and simulation-based exercises
- Mentor students on AI/ML projects and practical applications
- Collaborate with TAPMI faculty on course design, assessment, and AACSB/AoL requirements
- Contribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-making
Qualifications
Essential:
- Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field
- Demonstrated expertise in AI/ML, with teaching or corporate training experience
- Proficiency in Python, R, or equivalent programming environments for machine learning
Desirable:
- Industry or research experience in retail analytics, marketing analytics, or consumer insights
- Familiarity with AI/ML applications and optimization techniques in retail contexts
- Record of applied research, consulting, or publications in analytics-driven retail strategy
Skills and Competencies
- Ability to simplify complex technical concepts for management students
- Strong communication and classroom engagement skills
- Ability to bridge theory with real-world applications
- Collaborative mindset and commitment to academic excellence
Remuneration
Compensation will be commensurate with qualifications, experience, and profile , and in line with TAPMI’s norms for visiting faculty.
Application Process
Interested candidates may send their applications to Prof. Deepak A S ( ), Analytics Area Chair, with the subject line: “Application – Visiting Faculty (Data Analytics for Retail Decision-Making)”
The application should include:
- Detailed CV (with academic, teaching, and industry experience)
- List of two professional references