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Contract Business Intelligence Analyst/Data Scientist

Posted 2 days agoViewed

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💎 Seniority level: Senior, 5+ years

📍 Location: United States

💸 Salary: 70.0 - 80.0 USD per hour

🔍 Industry: Financial information and services

🏢 Company: The Motley Fool👥 501-1000💰 $25,000,000 Private about 15 years agoPublishingConsultingNewsFinancial ServicesMarketing

⏳ Experience: 5+ years

🪄 Skills: AWSPythonSQLData AnalysisMachine LearningMLFlowNLTKNumpyTableauPandasData visualization

Requirements:
  • Minimum 5 years of collaborative data analytics experience delivering insights to key stakeholders.
  • Knowledgeable in reporting and data visualization tools like Tableau, ThoughtSpot, or Power BI.
  • Demonstrated ability to influence data-informed decisions and drive growth in key metrics.
  • Intermediate to advanced technical data skills, including programming experience with Python, SQL proficiency, statistical testing and experiment design.
  • Supervised machine learning methods and approaches; ML project deployment.
  • Familiarity with common data science libraries (e.g., scikit-learn, pandas, NumPy).
  • Extensive experience with LLMs and NLP.
  • Leveraging and fine-tuning LLMs for automating business analysis.
  • Implementing NLP techniques to extract insights from large datasets.
  • Experience with AWS.
  • A continuous learner: someone who keeps up with the latest data science trends.
Responsibilities:
  • Collaborate with business teams to understand their strategies and translate them into data initiatives.
  • Provide data-informed recommendations to improve product features, engagement, and member experience.
  • Monitor key metrics and develop strategies to impact business performance positively.
  • Analyze large datasets to derive meaningful insights.
  • Perform exploratory data analysis to inform strategic initiatives.
  • Develop and maintain dashboards and reports for stakeholders.
  • Communicate complex data insights clearly and actionably.
  • Utilize advanced analytics techniques to identify trends and opportunities.
  • Apply statistical methods and machine learning algorithms to solve complex business problems.
  • Build predictive models for forecasting, marketing response, segmentation, and decision support.
  • Develop LLM-based solutions to enhance data interpretation and reporting.
  • Implement NLP techniques to process and analyze unstructured data.
  • Collaborate with data engineering to automate and operationalize models.
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