- Highly efficient in MLOps concepts and have experiences in product industrialization (from data science point of view). Experience in building product for live deployment, CI/CD.
- Proficient with cloud platforms like Azure, GCP, including their data management systems. Experienced in using Databricks for product deployment.
- Experience in ML projects involving techniques: Regression, Time Series, Clustering, Classification, Dimension Reduction, Anomaly detection with traditional ML approaches and DL approaches.
- Solid background in statistics, probability distributions, A/B testing validation, univariate/multivariate analysis, hypothesis test for different purpose, data augmentation etc.
- Clear algorithmic thinking, display clear logic in problem solving.
- Familiar with designing testing framework for different modelling practice/projects based on business needs.
- Exposure to Gen AI tools and enthusiastic about experimenting and have new ideas on what can be done.
- Understanding toward Gen AI models and techniques, GANs, transformers, vectorization, RAG etc.
- If they have improved an internal company process using an AI tool, that would be great (e.g. process simplification, manual task automation, auto emails)
- Ideally, 10+ years of experience, and have been on independent business facing roles.
- CPG or retail as a data scientist would be nice, but not number one priority, especially for those who have navigated through multiple industries.
- Being proactive and collaborative would be essential.
- Communication for success, stakeholder management, technical documentation, creating playbooks etc.
- Time management: Prioritization of tasks and work stream optimization.
- Basic understanding of regulations around use of data, able to map them to the actual tasks.
- Resource management, project planning according to data science project life cycles 3rd party management.
- Able to interact with project squad effectively considering the complex structure.
- Test new tools/platforms such as Copilot, Fabric for commercial reporting. Testing,
- validation and build trust.
- Building algorithms for predicting trend in category, consumptions to support dashboards.
- Revenue Growth Management, create/understand the algorithms behind the tools (can be built by 3rd parties) we need to maintain or choose to improve. Able to prioritize and build product roadmap. Able to design new solutions and articulate/quantify the limitation of the solutions.
- Demand forecasting, create localized forecasts to improve in store availability. Proper model monitoring for early detection of potential issues in the forecast focusing particularly on improving the end user experience.
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Mondelez International - Anywhere in India/Multiple Locations/Mumbai - Mondelez india foods private limited
Description
About the Role :
We are seeking a highly skilled and motivated Senior Data Scientist to support a big data program in North America. The successful candidate will play a pivotal role in supporting multiple projects in this program covering traditional tasks from revenue management, demand forecasting, improving customer experience to testing/using new tools/platforms such as Copilot Fabric for different purpose.
The expected candidate would have deep expertise in machine learning methodology and applications. And he/she should have completed multiple large scale data science projects (full cycle from ideation to BAU). Beyond technical expertise, problem solving in complex set-up will be key to the success for this role. This is a data science role directly embedded into the program/projects, stake holder management and collaborations with patterner are crucial to the success on this role (on top of the deep expertise).
What we are looking for :
