Responsibilities :

- Enable Data Science features within Planview applications by working in a fast-paced start-up mindset.

- Collaborate closely with product management to enable Data Science features that deliver significant value to customers, ensuring these features are also optimized for operational efficiency.

- Manage every stage of the AI/ML development lifecycle, from initial concept through deployment in a production environment.

- Design and implement optimization models (e.g., resource-constrained scheduling, portfolio/project selection, simulation-based decision support) to solve complex planning and allocation problems at enterprise scale.

- Contribute to agentic AI features - forecasting, risk-scoring, and recommendation models that power AI agents embedded in Planview products.

- Provide leadership to other Data Scientists by exemplifying exceptional quality in work, nurturing a culture of continuous learning, and offering daily guidance in their research endeavors.

- Effectively communicate ideas drawn from complex data with clarity and insight.

Required Qualifications :

- Master's in Operations Research, Statistics, Computer Science, Data Science, or related field.

- 8+ years of experience as a data scientist, data engineer, or ML engineer.

- Demonstrable history bringing Data Science features to Enterprise applications.

- Exceptional Python and SQL coding skills.

- Strong grounding in Optimization (linear/integer programming, simulated annealing, heuristics, or similar) alongside Machine Learning, Generative AI, NLP, Statistics, and Simulation.

- Experience with AWS Data and ML Technologies (SageMaker, Glue, Athena, Redshift).

- Experience designing and building tool/service interfaces that other systems (including AI agents) can invoke reliably

- API/service contract design, schema definition, and testing discipline.

- Working understanding of agentic AI system architecture - how agents discover and call tools, how actions are scoped and tracked, and how outputs feed back into planning workflows.

Preferred Qualifications :

- Experience working with datasets in the domain of project management, software development, and resource planning.

- Experience with common libraries and frameworks in data science (Scikit Learn, TensorFlow, PyTorch).

- Experience with ML platform tools (AWS SageMaker).

- Hands-on experience with MCP (Model Context Protocol) or similar tool-calling/agent-orchestration standards (e.g., A2A, LangChain tool interfaces).

- Skilled at working as part of a global, diverse workforce of high-performing individuals.

- AWS Certification is a plus.