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Strong employer brand, popular Data Scientist title, mid-level (1–4 years) and broad skill requirements.
Skills like SQL, Python, Power BI, and data-lake experience are highly transferable across industries.
Explicit 1–4 year requirement plus mandatory SQL, Power BI, Python, CRM, and data lake skills.
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Transform complex datasets into actionable insights supporting Customer Experience (CX), CRM Analytics, and business intelligence.
Develop and maintain interactive Power BI dashboards and reports on customer experience metrics and business performance.
Leverage Data Lake technologies and AI/GenAI tools to automate reporting, enhance data quality, and drive operational efficiency.
1–4 years of experience in Business Intelligence, Data Analytics, Customer Experience Analytics, or related field.
Strong proficiency in SQL; good working knowledge of Python; advanced Excel skills; experience with Power BI dashboard development.
Experience with Data Lake environments (Amazon Redshift, Amazon Athena) and CRM platforms (Salesforce, Medallia).
Experience using AI tools (e.g., ChatGPT, Microsoft Copilot, Salesforce Einstein) to enhance analytics workflows.
Experienced in customer journey and behavioral data analysis partnered with CX, Business, and Product teams.
Ability to independently design, develop, and deploy reporting solutions with high accuracy and usability.
Skilled in data transformation, entity resolution, and cross-functional stakeholder collaboration in cloud-based environments.