IBM AI-Driven Threat Detection Engineer
Job Title: Data Scientist Pricing Automation & Optimization Reports To: Sr. Manager, Data Scientist Pricing Automation & Optimization Data Science Leader Position Summary
We are seeking a Data Scientist to lead cross-functional AI/ML initiatives and drive our enterprise-wide AI vision and strategy. This role is a bridge between tactical execution and long-term strategic planning, requiring a visionary who can work independently and collaboratively with data analytics professionals across and outside OpenKyber to deliver transformative AI/ML solutions. The Data Scientist will frequently interface with senior stakeholders, providing thought leadership and regular updates on key analytics initiatives. This position demands top-tier technical expertise in machine learning & generative AI, combined with exceptional written and oral communication skills. The ideal candidate is a proven leader who pairs expert-level modeling and software engineering skills with outstanding stakeholder management and strategic program leadership.
Essential Responsibilities:
• Own end-to-end model development for pricing, demand forecasting, and elasticity estimation; productionize models in Azure ML and Databricks.
• Implement prescriptive analytics through optimization with Linear Programming, Mixed Integer Programming or Reinforcement Learning.
• Implement and maintain feature stores, model monitoring workflows, and drift checks using MLflow (metrics, alerts, lineage).
• Design and execute A/B tests or quasi-experiments to measure revenue, pricing uplift, and PCP attach rate impact.
• Apply SHAP/LIME and other model interpretability tools to explain drivers of model behavior to Revenue Management partners.
• Contribute to CI/CD workflows (Azure DevOps), support data contracts with Data Engineering, and develop scalable API and batch-serving patterns.
• Communicate insights, assumptions, risks, and trade-offs in clear, concise, and executive-ready narratives.
Qualifications / Knowledge / Skills: 2 - 4 years of hands-on Data Science experience delivering production-grade ML solutions. Proficiency in Python (scikitlearn, XGBoost), Spark/Delta, SQL, Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus. Strong understanding of experimental design, statistical testing, and causal inference basics. Ability to translate technical concepts into actionable business insights; skilled in stakeholder alignment and cross-functional communication.
Expectations by Dimension
• Predictive Modeling (ML): Strong practitioner with experience in time series forecasting, price elasticity modeling, and panel data techniques.
• Prescriptive Modeling (Optimization / OR): Foundational familiarity with linear and mixed-integer programming; experience or exposure to ORTools, Gurobi, or related optimizers.
• Model Explainability: Working-level proficiency with SHAP, LIME, and other model transparency frameworks.
• Software Engineering Skills: Writes modular, maintainable code; participates in code reviews; implements unit and integration tests.
• A/B Testing & Experimentation: Designs experiments with senior review; able to calculate significance, power, and interpret test outcomes.
• Change Management & Communication: Provides regular updates to business partners; comfortable addressing stakeholder questions and concerns.
For applications and inquiries, contact: [email protected]
Apply Now
Apply Now
We are seeking a Data Scientist to lead cross-functional AI/ML initiatives and drive our enterprise-wide AI vision and strategy. This role is a bridge between tactical execution and long-term strategic planning, requiring a visionary who can work independently and collaboratively with data analytics professionals across and outside OpenKyber to deliver transformative AI/ML solutions. The Data Scientist will frequently interface with senior stakeholders, providing thought leadership and regular updates on key analytics initiatives. This position demands top-tier technical expertise in machine learning & generative AI, combined with exceptional written and oral communication skills. The ideal candidate is a proven leader who pairs expert-level modeling and software engineering skills with outstanding stakeholder management and strategic program leadership.
Essential Responsibilities:
• Own end-to-end model development for pricing, demand forecasting, and elasticity estimation; productionize models in Azure ML and Databricks.
• Implement prescriptive analytics through optimization with Linear Programming, Mixed Integer Programming or Reinforcement Learning.
• Implement and maintain feature stores, model monitoring workflows, and drift checks using MLflow (metrics, alerts, lineage).
• Design and execute A/B tests or quasi-experiments to measure revenue, pricing uplift, and PCP attach rate impact.
• Apply SHAP/LIME and other model interpretability tools to explain drivers of model behavior to Revenue Management partners.
• Contribute to CI/CD workflows (Azure DevOps), support data contracts with Data Engineering, and develop scalable API and batch-serving patterns.
• Communicate insights, assumptions, risks, and trade-offs in clear, concise, and executive-ready narratives.
Qualifications / Knowledge / Skills: 2 - 4 years of hands-on Data Science experience delivering production-grade ML solutions. Proficiency in Python (scikitlearn, XGBoost), Spark/Delta, SQL, Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus. Strong understanding of experimental design, statistical testing, and causal inference basics. Ability to translate technical concepts into actionable business insights; skilled in stakeholder alignment and cross-functional communication.
Expectations by Dimension
• Predictive Modeling (ML): Strong practitioner with experience in time series forecasting, price elasticity modeling, and panel data techniques.
• Prescriptive Modeling (Optimization / OR): Foundational familiarity with linear and mixed-integer programming; experience or exposure to ORTools, Gurobi, or related optimizers.
• Model Explainability: Working-level proficiency with SHAP, LIME, and other model transparency frameworks.
• Software Engineering Skills: Writes modular, maintainable code; participates in code reviews; implements unit and integration tests.
• A/B Testing & Experimentation: Designs experiments with senior review; able to calculate significance, power, and interpret test outcomes.
• Change Management & Communication: Provides regular updates to business partners; comfortable addressing stakeholder questions and concerns.
For applications and inquiries, contact: [email protected]
Apply Now
Apply Now