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Tier-1 brand, metro location, popular Data Scientist title and mid-level experience increase applicant competition.
Core ML and data engineering skills are broadly transferable across industries, though automotive experience helps.
Explicit 4+ years requirement plus mandated Python, SQL, data engineering and ML skills increases filter strictness.
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Own end-to-end analytics project lifecycle: problem definition, data engineering, model development, validation, deployment, and reporting.
Translate business problems into analytical solutions using Python, SQL, Google Cloud, and big data tools like Hadoop.
Collaborate cross-functionally to deliver analytic products, maintain quality, implement change management, and provide training to business teams.
Bachelor’s degree in Statistics, Data Science, Computer Science, or related quantitative field.
4+ years of experience in analytics involving data mining, statistical analysis, modeling, and optimization.
3+ years experience with data engineering using SQL, ETL/ELT, and python for data cleaning and wrangling.
Work Experience Required: 4+ years; Industry experience: Not explicitly mentioned as mandatory (automotive industry experience is a plus).
Experienced with full data science project delivery and comfortable navigating vaguely defined problems.
Strong cross-functional communicator capable of advocating technical solutions to varied audiences.
Shown ability to independently manage analytics projects and maintain high quality deliverables in collaboration with business stakeholders.