- 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 analytics, business intelligence, experimentation, optimization, AI/ML, and automation.
- 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 Planning & Operations.
- Utilize expertise in machine learning, statistics, and automation to develop analytics solutions.
- Deploy models to production, ensuring they operate reliably and efficiently at a large scale.
- Continuously monitor and update models to adapt to new data or changes in data patterns.
- 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.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- MS degree in Computer Science, Mathematics, Statistics, Operations Research, or a related field.
- 8+ years of experience managing and analyzing large-scale data using Python, R, or similar languages.
- 8+ years of experience with SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling.
- 8+ years of experience analyzing and interpreting data, developing metrics, drawing conclusions, recommending actions, and reporting results across stakeholders.
- Proven track record of managing and leading cross-functional projects and teams.
- Proven 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.
- 8+ years of experience in model building and algorithm development for machine learning, statistics, and simulation.
- Experience in putting ML models into production and continuous monitoring and improvement.
- Familiarity with object-oriented programming languages (such as C++ or Java) and visualization tools (such as Tableau)
- Knowledge of simulation and optimization techniques
- Experience with GIS (geographic information systems), including collecting, managing, analyzing, modeling, and presenting geographic or spatial data.
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