Data Scientist

Responsibilities

• Collaborate with cross-functional data and business teams to define problems, analyze impacts, identify opportunities, and develop solutions that improve decision-making and efficiency.
• Translate business challenges into data-driven problems and design appropriate data science solutions, including metrics, analytics, business intelligence, and experimentation.
• Identify operational gaps, build analytical models to derive insights, and support decision-making across organizational leadership.
• Design and implement statistical models such as hypothesis testing, forecasting, statistical process control, and simulation to influence critical business decisions and Data Center operations.
• Utilize expertise in statistics, machine learning, optimization, and automation to develop analytics solutions.
• Work closely with stakeholders, data engineers, and program/product managers to ensure seamless progress.
• Educate and influence stakeholders to enhance operational efficiency with empathy.
• Recommend process improvements based on operational data and user behavior to boost business performance.
• Mentor team members on data science best practices.

Qualifications

• 6+ years of experience (2 years+ post Ph.D.) with advanced SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling.
• 6+ years of experience (2 years+ post Ph.D.) managing and analyzing large-scale data using Python, R, or similar languages.
• 6+ years of experience (2 years+ post Ph.D.) working with visualization tools such as Tableau, PowerBI, or similar.
• 6+ years of experience (2 years+ post Ph.D.) analyzing and interpreting data, developing metrics, drawing conclusions, recommending actions, and reporting results across stakeholders.
• Experience in enhancing data collection procedures, data processing, cleansing, and verifying data integrity.
• Proven track record of managing and leading cross-functional projects and teams.
• Solid understanding of machine learning techniques and algorithms.
• Hands-on programming experience in one or more of: AI/ML, LLM, NLP, Statistical modeling.
• Proficient in statistical analysis and experimental design.

Preferred Qualifications

• Knowledge of simulation and optimization techniques.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact.
• Technical knowledge of data center operations.
• Experience adhering to and implementing responsible, ethical AI practices.
• Great communication and storytelling skills to influence all organizational levels.
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration).
• Master's degree in Computer Science, Engineering, Mathematics, Statistics, Operations Research, or a related analytical field.