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Tier-1 brand, metro location, mid-level generalist ML role with broad skillset increases competition.
Requires conversational AI, support-data and measurement-framework expertise, reducing cross-industry transferability.
Explicit 5-7 years, Master's/PhD, and many mandatory ML, statistics and platform skills make filters strict.
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Develop and implement advanced data collection and analytics systems to optimize statistical efficiency and measure business outcomes.
Apply machine learning and statistical models to analyze complex customer journey data and drive predictive, proactive support solutions.
Collaborate with cross-functional teams including Data Engineering to build scalable data solutions and create impactful visualizations and dashboards for diverse audiences.
Master’s or PhD degree in business administration, economics, computer science, management information systems, or related field or equivalent experience.
5-7+ years of experience in Data Science, Machine Learning, or Applied Research in measurement frameworks or systems.
Proficiency in machine learning, statistical modeling, data mining, Python programming, and advanced dashboarding (Power BI preferred).
Hybrid work model requirement: approximately 2 days per week onsite at HPE office.
Experienced in working with customer support data, conversational AI logs, and omnichannel analytics with advanced modeling techniques like Higher Order Markov Chain and Hazard Models.
Demonstrated ability to collaborate with engineering and business teams to translate data insights into business transformation and measurable value.
Skilled in designing scalable data models and working closely with Data Engineering on platforms like Snowflake and Databricks for analytics and AI workloads.