Associate Data Scientist
Reliance Health
PythonPyTorchScikit-LearnSQLTableauTensorflow
Job Level
Mid-LevelSenior
Tech Stack
PythonScikit-LearnSQLTensorflow
About the role
- Own the ML Roadmap: Define and prioritize product features and enhancements related to ML-based forecasting and prediction in the supply chain context.
- Bridge Business and Technology: Collaborate with stakeholders across Lyric, including business leaders, customers, data scientists, and engineers, to understand needs and translate them into scalable ML solutions.
- Forecasting & Predictive Modeling: Work with the data science team to design, implement, and refine machine learning models that predict demand, optimize inventory levels, and forecast supply chain disruptions.
- Data-Driven Insights: Lead initiatives to incorporate predictive analytics into the Lyric Supply Chain Platform, enabling users to make proactive, data-informed decisions.
- User-Centric Design: Ensure the ML features are intuitive, actionable, and seamlessly integrated into the existing platform. Drive customer feedback loops to continuously refine the forecasting tools.
- Technical Collaboration: Coordinate with engineering teams to implement and scale machine learning models, ensuring high performance and reliability.
- Performance Metrics: Define key success metrics for ML-driven features, monitor model performance, and optimize outcomes through ongoing iterations.
- Stay Ahead of Trends: Keep up-to-date with the latest trends and developments in machine learning, AI, and supply chain management to identify new opportunities for innovation.
- Documentation & Reporting: Provide comprehensive documentation of ML models, forecasts, and analytical methods for internal teams and external stakeholders.
Requirements
- 5+ years of product management experience, preferably in machine learning or data-driven product development.
- Strong understanding of ML/AI techniques, especially in forecasting and predictive modeling, including regression models, time-series analysis, and demand forecasting.
- Hands-on experience with data science tools (e.g., Python, R, SQL) and ML frameworks (e.g., TensorFlow, Scikit-learn).
- Proven track record of launching and scaling ML/AI-based products, ideally in SaaS or enterprise environments.
- Excellent ability to translate complex technical concepts into business outcomes and vice versa.
- Strong analytical, problem-solving, and decision-making skills.
- Experience with Agile methodologies and product lifecycle management tools (e.g., JIRA, Confluence).
- Exceptional communication and stakeholder management skills, with a focus on driving alignment across cross-functional teams.
- Bachelor's or Master’s degree in a technical field such as Computer Science, Engineering, Data Science, or a related discipline. An MBA or relevant business experience is a plus.
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