General Mills
Location
Mumbai | India
Job description
Data Scientist II - Decision Sciences
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 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, digital & technology, innovation, technology & quality, consumer & market intelligence, sales strategy & intelligence, global shared services, finance shared services and Human Resources Shared Services.For more details check out
Job Overview
The future of food will be created by those who best anticipate evolving consumer behavior. Consumer & Market Insights (CMI) collects, curates, and combines data, human behavior understanding, and empathy to achieve competitive advantage for General Mills.
Our mission in CMI 'globally' is to be the spark that ignites growth acceleration, connecting insights and analytics to drive action.
We drive business growth through a deep understanding of our consumers and our markets. Our goal is to illuminate growth opportunities and guide teams to activate behind them through consumer-led strategies and ideas.
CMI Mumbai is an extension of General Mills CMI global organization, working closely with Growth Analytics & Foresights central teams, and all our GMI business segments i.e. North America Retail, Pet, International and North America Food Service, along with the CPW business (GMI's JV with Nestle). We are a young and dynamic team of 100 and growing, with research, data, and analytical skills, with the unique opportunity to shape and scale capabilities across our global organization
This position is a part of the Consumer and Market Intelligence, Decision Sciences team, Mumbai. This is a global team of 90 members supporting business and enabling strategies through data-driven solutions. Team is based out of Minneapolis Minnesota and Mumbai India location.
Our Decision Sciences team is made of data engineers, data visualisers, statisticians and data scientists who help model and predict the impact of multiple internal and external forces on our businesses for strategic decision-making.
We are looking for a data scientist
· who is passionate about the possibilities of leveraging data for informed decision-making and has demonstrated and implemented a few of those.
· who not only understands the data, the model, and the math but also its necessity & impact on business.
· who loves to speak with stakeholders, understand the business, and then proactively identify opportunities when ML can bring in significant value.
Key Accountabilities
1. Develop innovative approaches to assist business partners in achieving objectives through analysis and modelling.
2. Think creatively to identify and test new sources of information that unlock additional business value.
3. Curate and connect external datasets for widespread enterprise-wide analytical usage.
4. Effectively communicate the 'why and how' of data-driven recommendations to cross-functional teams, employing storytelling techniques.
5. Engineer features by leveraging business acumen to categorize, aggregate, pivot, or encode data for optimal results.
6. Utilize machine learning to develop repeatable, dynamic, and scalable models.
7. Passionately advocate for and educate others on the value and significance of data-driven decision-making and analytical methods.
8. Identify and develop long-term data science processes, frameworks, tools, and standards.
9. Collaborate as a member of the team, actively engaging with and seeking feedback from other Data Scientists.
10. Be able to explore and troubleshoot niche technologies and provide automation solutions.
Minimum Qualifications
1. Should have a working knowledge of traditional ML and statistical models, not just DL.
2. Experience working with time series/forecasting solutions.
3. Experience in working with unsupervised NLP tasks is a bonus.
4. Proficient in R and/or Python and SQL. Good knowledge of Bigdata and Cloud Platforms.
5. Minimum of 4 years of related experience with a bachelor's degree; or 3 years with a master's degree.
6. Proficient in executing clustering, regression, and classification techniques with minimal guidance.
7. Experience in building machine learning, deep learning, and artificial intelligence applications/tools.
Preferred Qualifications/ Skills/ Job Experiences
1. Develops analytic solution framework and executes them.
2. Outstanding stakeholder management skills.
3. Understanding/experience in the CPG industry is desirable.
4. Wholesome thinking -not just ML models but also business strategies and analytical products.
5. Creates stakeholder-ready deliverables and presents them to stakeholders with minimal guidance.
6. Experience in basic statistical analysis, modelling, clustering, and data mining techniques to identify trends and insights.
7. Technical understanding of cloud platforms and the ability to utilize data from various sources such as BigQuery, flat files, and cloud storage.
8. Strong number sense and ability to identify questionable data, investigate it, and address any issues.
9. Exemplary organizational skills with attention to detail and accuracy.
10. Familiarity with data visualization tools.
11. Proficiency in writing complex SQL queries.
12. ML-based smart application development (R-shiny/Flask etc.)
13. Ability to comprehend business use cases and translate them into data science problems.
14. Capability to effectively explain model output to business stakeholders and instill trust in the model.
15. Effective communication and a team player.
16. Curiosity despite having developed expertise.
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