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Strong employer brand, metro location, mid-level data scientist title, and common skillset drive high competition.
Core data science and analytics skills transfer across industries, though Celonis process-mining domain adds some specificity.
Explicit 3+ years requirement plus mandatory SQL/Python and analytics tool experience makes shortlisting moderately strict.
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Develop and communicate data-driven insights and decision-making applications focused on operational processes.
Build, document, and maintain automated operational process improvements with emphasis on data accuracy and integrity.
Collaborate with stakeholders across engineering, management, and executive levels to facilitate data-driven discussions and support strategic and tactical decisions.
Bachelor’s degree or equivalent in Economics, Business, Mathematics, Computer Science, or Data Science.
Minimum 3 years experience in Analytics Engineering, Product Analysis, or Data Engineering roles within SaaS or enterprise software contexts.
Proficiency in analytic tools such as Celonis EMS, Tableau, Qlik, Looker or Power BI, and programming with SQL, Python, and Pandas.
Experience working with large datasets and agile methodologies using tools like Jira.
Experienced in cross-functional collaboration with product, engineering, and growth teams to drive analytic insights.
Skilled in building and operationalizing statistical and machine learning models within fast-growth enterprise environments.
Strong in managing data integrity and automation in complex, large-scale datasets to enable scalable business insights.