Job Description Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It With Pride. You will help our business react to changing business conditions with excellent data analysis. You will define the requirements, perform the analysis and identify patterns in large amounts of data. Key responsibilities: - Support o9 model build phase covering EDA, Feature Engg, Experimentation, slicing strategy, parameter tuning and reports review in coordination with RDS - Support resolving model input data defects in coordination with Data Science Leads, BU DP Champions and Data Stewards - Perform experiments supporting value to o9 model building on o9 experiment zone/tenant - Participate in o9 Data Science trainings and upskilling plan - Support Achilles project to harmonize the forecast granularity, driver ingestion and experimentation - Support during integration testing and user testing for specific business units in scope - Support BU wise Data Qulaity Imporvement track - Build long term sustainable plan for AI/ML Model runs for the specific BU in scope More about this role Technical requirements: - Experience in any Data Science language like Python, Spark/Pyspark, SparkML, R, o9 - Experience with Cloud solutions (GCP), Bigquery, Uniy Catalog and deployment of data science models in production environment. - Knowledge and experience in data science cloud platforms like o9 solutions, Databricks or similar. - Knowledge of analytical techniques in statistical modelling, machine learning with exposure to forecasting domain especially driver-based forecasting - Basic understanding of supply chain processes - Should be able to articulate data science outcome into business understandable language. - Experience developing and deploying high standard Statistical and/or machine learning solution. - Agile project management experience, good stakeholder management, vendor management skills - 6+ years of experience in data science or advance analytics roles - Bachelors or masters degree in Engineering, Statistics, Data science, data analytics or relevant fields No Relocation support available Business Unit Summary At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about. We have a rich portfolio of strong brands globally and locally including many household names such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum. Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen-and happen fast. Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. Job Type Regular Data Science Analytics & Data Science

• Designing and implementing state of the art Large Language Model (LLM) based agents • Using advanced Generative AI techniques deriving actionable insights from unstructured text data • Predicting client interest basis their digital footprint • Leverage statistical and machine learning techniques to extract actionable insights from client retention data • Develop customer churn prediction models • Build tools to process structured and unstructured data

• Design and maintain a scalable data model integrating product usage and telemetry data, customer success and support signals, and revenue data such as ARR, MRR, renewals, and pipeline • Align and normalize data across systems, including Salesforce, product systems, and support tools • Build clean, reusable datasets for analytics and BI • Define and standardize core SaaS metrics, including Net Revenue Retention (NRR), Gross Revenue Retention (GRR), expansion, contraction, churn, renewal forecasting, and pipeline coverage • Partner with Customer Success, Revenue Operations, Sales, and Finance teams to drive revenue insights • Build models to forecast usage and revenue growth, predict expansion likelihood, and identify churn and saturation risk • Apply statistical and analytical techniques such as time-series modeling, cohort analysis, regression, and probability modeling • Design dashboards in Tableau that connect product usage to revenue outcomes, surface expansion-ready and at-risk accounts, and provide visibility into renewal pipeline and performance • Ensure consistency through centralized metric definitions and SQL logic

• Lead Data Management Activities • Perform Training and Client Relationship Management • Develop and maintain Data Management Project Plan • Document deviations from the Plan, log and report issues • Primary contact for data management activities • Responsible for planning and implementing data management timelines • Assist with study-level resource planning • Provide training to new data management personnel • Perform QC review of work performed by less experienced data management personnel • Create and maintain clinical trial Data Management Study Binders