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data scientist (quant research) - gm data & ai lab Jobs in Mumbai

data scientist (quant research) - gm data & ai lab

data scientist associate - fraud risk Jobs in Mumbai

data scientist associate - fraud risk

senior data engineer

data scientist

Unilever

<div>
 
 Job Title:
 
 Data Scientist
 
 
 
 Function:
 
 Supply Chain
 
 
 
 Location:
 
 Mumbai HO
 
 
 
 Req ID:
 
 R-1171037
 
 
 
 Overview
 
 
 
 We are seeking a highly skilled Data Scientist to join our E-commerce FMCG team. This role is pivotal in leveraging data-driven insights to optimize supply chain, customer experience, and commercial performance. The Data Scientist will work closely with cross-functional teams to design predictive models, analyse consumer behaviour, and unlock opportunities that drive growth in the fast-paced FMCG e-commerce environment.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Data Analysis &amp; Insights: Collect, clean, and analyse large datasets from multiple sources (sales, supply chain, customer behaviour) to generate actionable insights.
 </li>
 <li>
 Predictive Modelling: Develop and deploy machine learning models to forecast demand, optimize inventory, and improve product availability.
 </li>
 <li>
 Supply Chain Optimization: Use advanced analytics to identify inefficiencies, reduce stock-outs, and improve On-Time-In-Full (OTIF) performance.
 </li>
 <li>
 Dashboard Development: Build and maintain MIS dashboards to monitor KPIs such as fill rate, in-stock %, inventory days on hand, and customer service metrics.
 </li>
 <li>
 Cross-Functional Collaboration: Partner with E-commerce, Supply Planning, Customer Operations, and IT teams to deliver scalable data solutions.
 </li>
 <li>
 Innovation &amp; Capability Building: Stay updated with industry trends, tools, and techniques to continuously enhance analytics capabilities.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s/master&rsquo;s degree in data science, Statistics, Computer Science, or related field
 </li>
 <li>
 3&ndash;5 years of experience in data science, preferably in FMCG or e-commerce
 </li>
 <li>
 Strong proficiency in Python/R, SQL, and data visualization tools (Power BI, Tableau, etc.)
 </li>
 <li>
 Experience with machine learning frameworks
 </li>
 <li>
 Solid understanding of supply chain, retail, or FMCG business models
 </li>
 <li>
 Excellent problem-solving, communication, and stakeholder management skills
 
 
 </li>
 </ul>
 All official offers from Unilever are issued only via our Applicant Tracking System (ATS). Offers from individuals or unofficial sources may be fraudulent - please verify before proceeding
</div>

Data Scientist

Dholakia Lab Grown Diamond

<div>
 
 
 Job Title:
 
 Data Scientist &ndash; Jewellery Manufacturing &amp; Retail Analytics
 
 
 
 
 
 
 Experience:
 
 2&ndash;6 years
 
 
 
 Location:
 
 Surat / Mumbai
 
 
 
 Industry:
 
 Diamond and Jewellery Manufacturing &amp; Retail
 
 
 
 
 
 
 Role Overview
 
 
 
 We&rsquo;re looking for a
 
 Data Scientist with a strong business mindset
 
 to solve real-world problems in the jewellery value chain &mdash; not just build models.
 
 
 This role sits at the intersection of
 
 data, finance, supply chain, and leadership
 
 . You&rsquo;ll work on demand forecasting, pricing, inventory optimisation, and margin analysis while accounting for
 
 gold price volatility, seasonality, festivals, promotions, and regional demand patterns
 
 .
 
 
 
 
 
 If you enjoy turning messy, operational data into clear business decisions, this role is for you.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Build and maintain
 
 demand forecasting models
 
 considering seasonality, festivals, promotions, and regional trends
 </li>
 <li>
 Develop
 
 pricing and margin models
 
 factoring gold rate volatility, labour costs, and BOM structures
 </li>
 <li>
 Optimise
 
 inventory planning
 
 for weight-based SKUs (grams, carats, designs, variants)
 </li>
 <li>
 Perform
 
 profitability and contribution analysis
 
 at SKU, category, and channel levels
 </li>
 <li>
 Partner closely with
 
 finance, supply chain, sales, and senior leadership
 
 to translate insights into actions
 </li>
 <li>
 Create clear dashboards, analyses, and narratives that support
 
 executive decision-making
 
 </li>
 <li>
 Continuously improve data quality, assumptions, and model performance based on real business feedback
 </li>
 </ul>
 
 
 
 
 
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 2&ndash;6 years of experience as a
 
 Data Scientist / Analytics professional
 
 </li>
 <li>
 Strong hands-on experience with
 
 Python
 
 (Pandas, NumPy, Scikit-learn)
 </li>
 <li>
 Solid knowledge of
 
 statistics, regression, and time-series forecasting
 
 </li>
 <li>
 Proficiency in
 
 SQL
 
 and working with large, imperfect datasets
 </li>
 <li>
 Ability to explain complex analysis in
 
 simple business language
 
 </li>
 </ul>
 
 
 
 
 
 Good to Have (Strong Advantage)
 
 
 <ul>
 <li>
 Experience in
 
 retail, manufacturing, jewellery, FMCG, or consumer goods
 
 </li>
 <li>
 Exposure to
 
 weight-based inventory
 
 , costing, pricing, or BOM analytics
 </li>
 <li>
 Understanding of
 
 gold pricing, wastage, making charges, or multi-component SKUs
 
 </li>
 <li>
 Experience working directly with
 
 CXOs or business heads
 
 </li>
 </ul>
 
 
 
 
 
 What We Value
 
 
 <ul>
 <li>
 Business-first thinking over theoretical perfection
 </li>
 <li>
 Curiosity and ownership &mdash; you ask
 
 why
 
 , not just
 
 what
 
 </li>
 <li>
 Comfort working in ambiguity and evolving data environments
 </li>
 <li>
 Strong collaboration across non-technical teams
 </li>
 </ul>
 
 
 
 
 
 Why Join Us
 
 
 <ul>
 <li>
 Work on
 
 high-impact, real-world jewellery problems
 
 , not sandbox datasets
 </li>
 <li>
 Direct exposure to
 
 leadership decision-making
 
 </li>
 <li>
 Opportunity to shape how data drives pricing, inventory, and profitability at scale
 </li>
 <li>
 Fast-growing organisation with a strong focus on
 
 analytics-led growth
 
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
 </li>
 </ul>
 
 
</div>

LTIMindtree

<div>
 
 
 Skill:
 
 Data Scientist
 
 
 
 Location: Mumbai
 
 
 
 
 Experience:
 
 10 to 16 Years
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 
 Mandate Skills:
 
 
 
 Statistical &amp; Machine Learning
 
 : Proficient in building
 
 supervised learning models
 
 (e.g., regression, classification, decision trees, ensemble methods).
 
 <ul>
 <li>
 Skilled in
 
 unsupervised learning
 
 techniques (e.g., clustering, dimensionality reduction, anomaly detection).
 </li>
 <li>
 Ability to apply
 
 statistical methods
 
 for hypothesis testing, feature engineering, and model evaluation (
 
 ROC, AUC, precision-
 
 recall, etc.).
 </li>
 </ul>
 
 
 Programming &amp; Tools
 
 :
 
 Python, Jupyter Notebook
 
 s, and libraries such as
 
 scikit-learn
 
 ,
 
 pandas, NumPy
 
 .
 
 
 
 
 
 Primary Skills &ndash; Good To have
 
 <ol>
 <li>
 
 Teradata Expertise
 
 : Strong hands-on experience with
 
 Teradata SQL, ClearScape Analytics
 
 , and
 
 ModelOps
 
 for deploying and managing models at scale.
 </li>
 <li>
 
 Domain Knowledge
 
 : Insurance industry processes, risk modelling, and customer analytics.
 </li>
 </ol>
 
 
 
 
 Responsibilities:
 
 
 <ol>
 <li>
 Analyze large datasets and develop predictive models within Teradata Data Lake/Lakehouse environments.
 </li>
 <li>
 Write simple, efficient SQL queries and collaborate with data engineering teams to build and validate data pipelines with robust data checks.
 </li>
 <li>
 Prepare, clean, and standardize data for analysis and modelling.
 </li>
 <li>
 Build supervised and unsupervised ML models using Python and Jupyter Notebooks.
 </li>
 <li>
 Communicate insights through clear reports and visualizations
 </li>
 <li>
 Document processes and ensure data quality standards.
 </li>
 <li>
 Stay updated on emerging technologies to improve model performance and reliability.
 </li>
 </ol>
 
 
 
 
 
 
 
 Interested candidates, please share resumes on Shubhadha.Naik@ltimindtree.com
 
</div>

LTIMindtree Hiring for Data Scientist- Mumbai

JPMorganChase

<div>
 
 
 JOB DESCRIPTION
 
 
 
 
 Join the Fraud Data Science team at JPMC and help drive innovation in fraud identification and prevention. As part of our team, you will design, develop, and deploy cutting-edge AI/ML solutions&mdash;including graph analytics and Large Language Models (LLMs)&mdash;to tackle complex fraud challenges and deliver measurable business impact.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Develop and implement advanced machine learning models (supervised and unsupervised) for fraud detection and prevention.
 </li>
 <li>
 Build and maintain graph analytics solutions to uncover fraud patterns and relationships.
 </li>
 <li>
 Leverage big data and cloud platforms (e.g., AWS, Spark) to automate, scale, and productionalize analytical models/ AI ML tools.
 </li>
 <li>
 Collaborate with cross-functional teams to translate business needs into actionable data science solutions.
 </li>
 <li>
 Present insights and recommendations to stakeholders, clearly communicating technical results and business impact.
 </li>
 <li>
 Document processes and ensure governance compliance for all analytical solutions.
 
 
 </li>
 </ul>
 
 Required Qualifications:
 
 
 
 <ul>
 <li>
 Develop and implement advanced machine learning models (supervised and unsupervised) for fraud detection and prevention.
 </li>
 <li>
 Hands-on experience with supervised and unsupervised machine learning statistical models. Knowledge of Graph Analytics is a big plus.
 </li>
 <li>
 Experience with Large Language Models (LLM) and Agentic AI will be an added advantage; although not mandatory.
 </li>
 <li>
 Strong technical skills in Python, PySpark, SQL, and big data/cloud platforms.
 </li>
 <li>
 Excellent problem-solving and communication skills. Ability to communicate complex findings clearly in both written format and verbally to technical and non-technical audiences.
 </li>
 <li>
 3+ years of experience with Bachelor&rsquo;s or Master&rsquo;s in a quantitative field (Mathematics, Statistics, Economics, Computer Science, Engineering, etc.).
 
 
 </li>
 </ul>
 
 Required Qualifications:
 
 
 
 <ul>
 <li>
 Experience developing and deploying production-quality machine learning models.
 </li>
 <li>
 Familiarity with dashboarding tools (e.g., Tableau) and cloud services (AWS Sagemaker, Amazon EMR).
 
 
 </li>
 </ul>
 
 ABOUT US
 
 
 
 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
 
 
 We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 
 
 
 
 ABOUT THE TEAM
 
 
 
 
 Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.
 
 
 The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
</div>

Data Scientist Associate - Fraud Risk

BNP Paribas

<div>
 
 About BNP Paribas Group
 
 
 
 
 BNP Paribas is a top-ranking bank in Europe with an international profile. It operates in 71 countries and has almost 199 000 employees
 
 . The Group ranks highly in its three core areas of activity: Domestic Markets and International Financial Services (whose retail banking networks and financial services are grouped together under Retail Banking &amp; Services) and Corporate &amp; Institutional Banking, centred on corporate and institutional clients. The Group helps all of its clients (retail, associations, businesses, SMEs, large corporates and institutional) to implement their projects by providing them with services in financing, investment, savings and protection. In its Corporate &amp; Institutional Banking and International Financial Services activities, BNP Paribas enjoys leading positions in Europe, a strong presence in the Americas and has a solid and fast-growing network in the Asia/Pacific region.
 
 
 
 About BNP Paribas India Solutions
 
 
 
 Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, a leading bank in Europe with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 6000 employees, to provide support and develop best-in-class solutions.
 
 
 
 About Business Line/Function
 
 
 
 GM Data &amp; AI Lab leverages the power of Machine Learning and Deep learning to drive innovation in various business lines. Our primary goal is to harness the potential of vast amounts of structured and unstructured data to improve our services and provide value. Today we are a team of around 40+ Data Scientists based in Paris, London, Frankfurt, Lisbon, New York, Singapore and Mumbai.
 
 
 
 Job Title
 
 
 
 Data Scientist (Quant Research)
 
 
 
 Date
 
 
 
 Department:
 
 
 Front Office Support
 
 
 Location:
 
 
 Mumbai
 
 
 
 Business Line / Function
 
 
 
 Global Markets &ndash; Data &amp; AI Lab
 
 
 
 Reports To
 
 
 
 (Direct)
 
 
 
 Grade
 
 
 
 (if applicable)
 
 
 (Functional)
 
 
 
 Number Of Direct Reports
 
 
 
 NA
 
 
 
 Directorship / Registration
 
 
 
 NA
 
 
 Position Purpose
 
 
 Your work will center on designing and deploying AI solutions for time series forecasting, financial modeling, anomaly detection and other Quant related usecases. We use AI to discover patterns, classify information, and predict likelihoods. Our team works on building, refining, testing, and deploying these models to support various business use cases, ultimately driving business value and innovation.
 
 
 As a Data Scientist on our team, you can expect to work on challenging projects, collaborate with stakeholders to identify business problems, and have the opportunity to learn and grow with our team. A typical day may involve working on model development, meeting with stakeholders to discuss project requirements/updates, and brainstorming/debugging with colleagues on various technical aspects.
 
 
 At the Lab, we're passionate about staying at the forefront of AI research, bridging the gap between research &amp; industry to drive innovation and to make a real impact on our businesses.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop and maintain AI models on time series &amp; financial date for predictive modelling, including data collection, analysis, feature engineering, model development, evaluation, backtesting and monitoring.
 </li>
 <li>
 Identify areas for model improvement through independent research and analysis, and develop recommendations for updates and enhancements.
 </li>
 <li>
 Working with expert colleagues, Quant and business representatives to examine the results and keep models grounded in reality.
 </li>
 <li>
 Documenting each step of the development and informing decision makers by presenting them options and results.
 </li>
 <li>
 Ensure the integrity and security of data.
 </li>
 <li>
 Provide support for production models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones.
 
 
 </li>
 </ul>
 Technical &amp; Behavioral Competencies
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in a numeric subject with understanding of economics and markets (eg.: Economics with a speciality in Econometrics, Finance, Computer Science, Applied Maths, Engineering, Physics)
 </li>
 <li>
 Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning, Probability Theory and Linear Algebra.
 </li>
 <li>
 Knowledge of Monte Carlo Simulations, Bayesian modelling &amp; Causal Inference.
 </li>
 <li>
 Experience with Machine Learning &amp; Deep Learning concepts including data representations, neural network architectures, custom loss functions.
 </li>
 <li>
 Proven track record of building AI models on time-series &amp; financial data.
 </li>
 <li>
 Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, PyMC, statsmodels).
 </li>
 <li>
 Ability to write clear and concise code in python.
 </li>
 <li>
 Intellectually curious and willing to learn challenging concepts daily.
 
 
 </li>
 </ul>
 
 Skills Referential
 
 
 
 Behavioural Skills:
 
 
 Ability to collaborate / Teamwork
 
 
 Critical thinking
 
 
 Communication skills - oral &amp; written
 
 
 Attention to detail / rigor
 
 
 
 Transversal Skills
 
 
 
 Analytical Ability
 
 
 
 Education Level
 
 
 
 Bachelor Degree or equivalent
 
 
 Experience Level
 
 
 At least 2 years
</div>

Data Scientist (Quant Research) - GM Data & AI Lab

<div>
 At EY, you&rsquo;ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we&rsquo;re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
 
 
 
 EY GDS &ndash; Data and Analytics (D&amp;A) &ndash; Senior &ndash; Senior Data Scientist
 
 
 
 
 Role Overview:
 
 
 
 We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.
 
 
 
 Responsibilities:
 
 
 
 
 Your technical responsibilities:
 
 
 
 <ul>
 <li>
 Contribute to the design and implementation of state-of-the-art AI solutions.
 </li>
 <li>
 Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
 </li>
 <li>
 Collaborate with stakeholders to identify business opportunities and define AI project goals.
 </li>
 <li>
 Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
 </li>
 <li>
 Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
 </li>
 <li>
 Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
 </li>
 <li>
 Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
 </li>
 <li>
 Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
 </li>
 <li>
 Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
 </li>
 <li>
 Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
 </li>
 <li>
 Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
 </li>
 <li>
 Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
 </li>
 <li>
 Ensure compliance with data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
 
 
 </li>
 </ul>
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
 </li>
 <li>
 Minimum 3-7 years of experience in Data Science and Machine Learning.
 </li>
 <li>
 In-depth knowledge of machine learning, deep learning, and generative AI techniques.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
 </li>
 <li>
 Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
 </li>
 <li>
 Familiarity with computer vision techniques for image recognition, object detection, or image generation.
 </li>
 <li>
 Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
 </li>
 <li>
 Expertise in data engineering, including data curation, cleaning, and preprocessing.
 </li>
 <li>
 Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
 </li>
 <li>
 Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
 </li>
 <li>
 Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
 </li>
 <li>
 Understanding of data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Track record of driving innovation and staying updated with the latest AI research and advancements.
 
 
 </li>
 </ul>
 
 Good to Have Skills:
 
 
 
 <ul>
 <li>
 Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
 </li>
 <li>
 Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
 </li>
 <li>
 Implement CI/CD pipelines for streamlined model deployment and scaling processes.
 </li>
 <li>
 Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
 </li>
 <li>
 Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
 </li>
 <li>
 Implement monitoring and logging tools to ensure AI model performance and reliability.
 </li>
 <li>
 Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
 </li>
 <li>
 Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.
 
 
 </li>
 </ul>
 
 EY | Building a better working world
 
 
 
 EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
 
 
 Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
 
 
 Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
</div>

EY - GDS Consulting - AI And DATA - Gen AI - Senior

General Mills India

<div>
 Position Title
 
 
 Scientist II &ndash; Statistics
 
 
 Function/Group
 
 
 R&amp;D/Packaging
 
 
 Location
 
 
 Mumbai
 
 
 Shift Timing
 
 
 Regular
 
 
 Role Reports to
 
 
 Assistant Manager, Global Knowledge Solutions
 
 
 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 Haagen-Dazs, we have 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 http://www.generalmills.com
 
 
 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 &amp; Technology (D&amp;T) Innovation, Technology &amp; Quality (ITQ), Consumer and Market Intelligence (CMI), Sales Strategy &amp; Intelligence (SSI), Global Shared Services (GSS), Finance Shared Services (FSS) and Human Resources Shared Services (HRSS).For more details check out https://www.generalmills.co.in
 
 
 We advocate for advancing equity and inclusion to create more equitable workplaces and a better tomorrow.
 
 
 
 Job Overview
 
 
 
 
 Function Overview
 
 
 
 In partnership with our cross-functional partners, ITQ innovates and develops products that meet the ever-changing needs of our consumers and enables long-term business growth. We identify and develop technologies that shape and protect our businesses today and into the future. ITQ operates across three organizations: Global Applications, Capabilities COEs, and Shared Services &amp; Operations
 
 
 For more details about General Mills please visit this Link
 
 
 
 Purpose of the role
 
 
 
 The Global Knowledge Services (GKS) organization catalyzes the creation, transfer, and application of knowledge to ensure ITQ succeeds at its mission of driving internal and external innovation, developing differentiated technology, and engendering trust through food safety and quality.
 
 
 The scientists in the Statistics and Analytics Program Area will collaborate with US and India GKS team members to deliver high value statistical work that advances ITQ initiatives in consumer product research, health and nutrition science, research and development, and quality improvement.
 
 
 The Scientist II in this program area is expected to: take ownership of the projects, deep expertise in statistical methodologies, data analysis, and model development. They will be responsible for providing advanced statistical consulting services, developing analytics solutions, and supporting decision-making processes across various projects.
 
 
 
 Key Accountabilities
 
 
 
 <ul>
 <li>
 70%of Time-Excellent Technical Work
 </li>
 <li>
 Independently work on projects and take ownership of the deliverables.
 </li>
 <li>
 Provide expert statistical consulting and support to internal and external clients on various projects.
 </li>
 <li>
 Design, implement, and interpret statistical analyses, including hypothesis testing, regression analysis, experimental design, and multivariate analysis.
 </li>
 <li>
 Develop and validate statistical models for predictive and prescriptive analytics.
 </li>
 <li>
 Collaborate with cross-functional teams to translate complex data into actionable insights.
 </li>
 <li>
 Advise on best practices for data collection, quality control, and management.
 </li>
 <li>
 Develop effective strategies for programming and data analysis based on client consultations and project briefs.
 </li>
 <li>
 Create high-quality programs for data preparation, data cleaning, statistical analysis, and results validation.
 </li>
 <li>
 Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modeling.
 </li>
 <li>
 Effectively and efficiently use advanced statistical software (e.g., R, Python) in support of project work.
 </li>
 <li>
 Leveraging multiple data sets to discover new insights.
 </li>
 <li>
 Create accurate and clear summary tables, visualizations, reports, and models that convey the required information and insights.
 </li>
 <li>
 Prepare detailed reports, presentations, and publications to communicate findings and recommendations.
 </li>
 <li>
 Mentor and train team members on statistical techniques and software.
 
 
 </li>
 </ul>
 15% of Time-Client Consultation and Business Partnering
 
 
 <ul>
 <li>
 Work effectively with clients to identify client needs and success criteria, and translate into clear project objectives, timelines, and plans.
 </li>
 <li>
 Be responsive and timely in sharing project updates, responding to client queries, and delivering on project commitments.
 </li>
 <li>
 Clearly communicate analysis, conclusions, insights, and conclusions to clients using written reports and real-time meetings.
 
 
 </li>
 </ul>
 10% of Time-Innovation, Continuous Improvement (CI), and Personal Development
 
 
 <ul>
 <li>
 Learn and apply a CI mindset to work, seeking opportunities for improvements in efficiency and client value.
 </li>
 <li>
 Identify new resources, develop new methods, and seek external inspiration to drive innovations in our work processes.
 </li>
 <li>
 Continually build skills and knowledge in the fields of statistics, and the relevant sciences.
 
 
 </li>
 </ul>
 5% of Time-Administration
 
 
 <ul>
 <li>
 Participate in all required training (Safety, HR, Finance, CI, other) and actively GKS, and ITQ meetings, events, and activities.
 </li>
 <li>
 Complete other administrative tasks as required.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Minimum Degree Requirements: Ph.D. in Statistics from an accredited university
 </li>
 <li>
 Minimum 2 years of related experience required
 
 
 </li>
 </ul>
 
 Specific Job Experience Or Skills Needed
 
 
 
 <ul>
 <li>
 D. in Statistics or a closely related field.
 </li>
 <li>
 Extensive knowledge of statistical theories, methodologies, and software (e.g., R, Minitab, Python, SQL).
 </li>
 <li>
 Proven experience in applying statistical techniques to real-world problems across various industries.
 </li>
 <li>
 Strong problem-solving skills and the ability to work independently on complex projects.
 </li>
 <li>
 Excellent written and verbal communication skills, with the ability to present complex statistical concepts to non-technical audiences.
 </li>
 <li>
 Experience with large datasets, data mining, and machine learning is a plus.
 </li>
 <li>
 Working experience in GCP is a plus.
 </li>
 <li>
 Experience in working on a project from inception to end is desirable.
 
 
 </li>
 </ul>
 
 For Global Knowledge Solutions
 
 
 
 <ul>
 <li>
 Ability to effectively work cross-functionally with internal/global team members.
 </li>
 <li>
 High self-motivation, with the ability to work both independently and in teams.
 </li>
 <li>
 Excels at driving projects to completion, with attention to detail.
 </li>
 <li>
 Ability to exercise judgment in handling confidential and proprietary information.
 </li>
 <li>
 Ability to effectively prioritize, multi-task, and execute tasks according to a plan. Able to work on multiple priorities and projects simultaneously.
 </li>
 <li>
 Demonstrated creative problem-solving abilities, attention to detail, ability to &ldquo;think outside the box.&rdquo;
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Preferred Major Area of Study: Statistics
 </li>
 <li>
 Preferred Professional Certifications: R, Python
 </li>
 <li>
 Preferred 2 years of related experience
 
 
 </li>
 </ul>
 
 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 &mdash; 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&rsquo;s next.
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Scientist - II

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