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Tier-1 brand, mid-level generalist ML title, metro location, and broad toolset increase candidate competition.
Advanced ML and data engineering skills are transferable, but enterprise deployment focus adds moderate specificity.
Explicit degree requirement, 2–3 years experience, and advanced ML/deployment skillset make screening strict.
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Define analytics solution objectives and technical requirements based on business needs and advanced analytic models.
Build, develop, and enhance client analytic models using appropriate methodologies for structured and unstructured data to deliver business insights.
Embed analytic models into business processes with Application Developers and measure business performance; lead model enhancements and communicate solutions to stakeholders.
Advanced expertise in data science methodologies including neural nets, regression, cluster analysis, text mining, etc.
Proficiency in analytics software (R, SAS, SPSS, Python) and programming languages (Python, SQL, R, SAS, Java, Unix Shell scripting); working knowledge of Hadoop framework desired.
PhD in Statistics, Operations Research, Computer Science or equivalent preferred; alternatively Master’s degree with 2-3 years relevant experience.
Work Arrangement: Hybrid role requiring average 2 days per week onsite at HPE office.
Experienced technical contributor or project lead capable of independently solving complex analytics problems using advanced methods.
Skilled at translating business requirements into mathematical models yielding measurable business outcomes in client environments.
Proficient at collaborating cross-functionally to embed analytics in operational systems and communicate insights effectively to diverse stakeholders.