

Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist contract position for "X" months, offering a pay rate of "$X per hour." It requires strong SQL skills, experience with Tableau or Qliksense, and familiarity with Python or R for advanced analytics.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
616
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ποΈ - Date discovered
July 8, 2025
π - Project duration
Unknown
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ποΈ - Location type
Unknown
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
United States
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π§ - Skills detailed
#Data Quality #Data Science #ML (Machine Learning) #Documentation #Python #Data Accuracy #R #Data Pipeline #Scala #Data Integrity #SQL (Structured Query Language) #Data Wrangling #Tableau #Visualization #Data Analysis #Stories #ChatGPT #AI (Artificial Intelligence)
Role description
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About the Role
Weβre seeking a skilled Data Analyst with a passion for driving customer-centric growth. In this role, youβll design and maintain robust data pipelines, develop actionable dashboards, and uncover critical insights to optimize customer journeys from acquisition to retention. If you love turning complex data into compelling stories that guide marketing and product decisions, weβd love to hear from you.
Responsibilities
Design and Maintain E2E Data Pipelines:
β’ Develop and manage scalable end-to-end data pipelines, ensuring data accuracy and availability across customer acquisition and retention workflows.
Ensure Data Quality and Governance:
β’ Proactively monitor and resolve data integrity issues; establish standards and documentation to drive reliability and transparency in analytics processes.
Build Actionable Dashboards and Reporting Tools:
β’ Create and maintain intuitive dashboards (using Tableau or Qliksense) and automated reports to track key performance indicators, customer segments, and lifecycle metrics.
Optimize Customer Funnels and Journeys:
β’ Analyze acquisition and retention funnels to pinpoint key drop-off points; recommend strategies to enhance customer experiences and drive conversion.
Generate Descriptive and Predictive Customer Insights:
β’ Leverage statistical and machine learning methods to analyze customer behavior and lifecycle trends, predict churn and lifetime value, and surface actionable opportunities.
Translate Insights into Business Recommendations:
β’ Synthesize analytical findings into clear narratives and strategic recommendations that inform marketing and product decisions, especially during peak seasons.
Key Skills & Experience
β’ Strong SQL skills and experience with data wrangling tools.
β’ Expertise in data visualization tools such as Tableau or Qliksense.
β’ Demonstrated ability to apply descriptive and predictive analytics to real-world business problems.
β’ Familiarity with Python or R for advanced analytics.
β’ Comfort using generative AI tools (like ChatGPT) to accelerate SQL/R code creation and enhance reporting workflows.