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Mid-level, metro, generalist data role with broad ML and BI skills increases competition.
Data and ML skills are broadly transferable across industries, so background sensitivity is low.
Explicit 6-9 years plus required ML, Python, and BI tools makes shortlisting strict.
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Collaborate with business partners to translate requirements into data-driven questions and independently conduct data analyses using ML techniques to optimize KPIs.
Apply data modeling, visualization, and text mining to generate actionable business insights and communicate findings effectively to senior stakeholders.
Develop measurable action plans from analyses and innovate proof of concepts with minimal supervision to impact business decisions.
6-9 years of relevant work experience in Data Analytics and data handling.
Master’s Degree in a quantitative field such as Computer Science, Economics, Engineering, Mathematics, Finance, or Statistics.
Proficiency in Python for quantitative analysis and experience with visualization tools like Tableau or PowerBI.
Experience with machine learning techniques including Regression, Decision Trees, Random Forest, Classification, and SVM.
Experienced in independently managing analytics projects and engaging with clients for data interpretation and insights generation.
Skilled in advanced analytics and predictive modeling techniques applied to business problems.
Able to communicate complex analytical findings through storytelling and storyboarding to non-technical business stakeholders.