Responsibilities
- Work as the data strategist with business stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Proactively look for unsolved, data-rich, high-impact business problems and create new opportunities in the AI solutioning pipeline.
- Evaluate feedback and challenging issues gathered by the business and technical teams and transform them into tractable problems to resolve.
- Participate in research paper publishing, Applied AI Competitions; organize hackathons and knowledge conferences/webinars. Work with Principal Data/OR Scientists to devise solution roadmaps and KPIs.
- Design, develop and evaluate highly innovative DL/ML & Stats based models.
- Establish scalable, efficient, and automated processes for DL/ML model development, model validation and model implementation.
- Conduct feature engineering and implement DL/ML models into production by collaborating with software developers and machine learning engineers.
- Develop processes and tools to monitor and analyse model performance and data accuracy.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Aggregate data from multiple sources to provide a comprehensive assessment.
- Create reports, presentations, and process documents to display impactful results.
- Communicate solutions to stakeholders and implement improvements as needed to operational systems.
- Recommend go / no-go on problem statements based on preliminary data analysis in consultation with project stakeholders.
- Collaborate with AI Champion and Business Data Analyst to define and ratify data requirements and sources.
- Collaborate with AI Solution Managers, Principal Data Engineer, OR Scientist and Principal ML Engineer to build ML/DL models and data prototypes.
QualificationsExperience
2-5 years of experience in Python/ R/ Scala and Statistical Analysis, Machine learning (Supervised and Unsupervised learning Techniques), neural networks, Deep Learning Techniques, Time-series analysis, NLP and chatbot systems, Reinforcement Learning, Model Optimization. Working knowledge of software development languages. Knowledge of Cloud Technologies is beneficial.
Education Qualification
PhD/MS/MTech in Computer Science/EE/Applied Mathematics/Optimization/other relevant disciplines involving computing and optimization. Experience with Reinforcement Learning and GenAI is preferred.
