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Popular title, mid-level (2–4 yrs), metro location, and broad Python/PySpark skills increase applicant competition.
Skills (Python, PySpark, BI, Azure) are widely transferable across industries, lowering background sensitivity.
Explicit 2–4 years plus mandatory Python, PySpark and BI skills create strict shortlisting filters.
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Analyze large structured and unstructured datasets to identify actionable business insights and trends.
Build and optimize scalable data processing pipelines using PySpark; develop AI-driven analytical solutions.
Support client engagements by presenting data-driven recommendations and developing dashboards or visualizations.
2–4 years of experience in Data Science, Analytics, or related roles.
Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field.
Proficient in Python and PySpark; experience with SQL and data visualization tools like Power BI or Tableau.
Exposure to AI and Generative AI concepts preferred; experience in a consulting or professional services environment preferred.
Experienced in handling big data analytics and building scalable data processing workflows using PySpark.
Capable of translating complex business requirements into data-driven solutions in a client-facing consulting context.
Skilled in both technical data science tasks and communicating findings effectively to technical and non-technical audiences.