Data Scientist (Fractional)
August 8
🏡 Remote – New York
Description
• Lead end-to-end data science projects, from defining objectives to data collection, exploration, model development, validation, and deployment. • Collaborate with domain experts and business stakeholders to understand revenue-related challenges and formulate data-driven solutions. • Apply advanced statistical and machine learning techniques to analyze large datasets. • Develop predictive and prescriptive models to forecast customer behavior, optimize pricing strategies, and enhance customer engagement. • Clean, preprocess, and manipulate data to ensure data quality and suitability for analysis and modeling. • Visualize findings and insights to effectively communicate results to both technical and non-technical audiences. • Mentor junior data scientists, providing technical guidance, fostering skill development, and promoting a culture of innovation.
Requirements
• Master's or Ph.D. degree in Data Science, Computer Science, Statistics, or a related field. • 7+ years of hands-on experience in data science, working with large datasets, and applying advanced analytical methods. • Proficiency in programming languages such as Python or R. • Extensive experience with machine learning algorithms, model development, and evaluation techniques. • Strong knowledge of statistical analysis, hypothesis testing, and experiment design. • Proficiency in data visualization tools such as Matplotlib, Seaborn, or similar libraries. • Experience with SQL and relational databases for data extraction and manipulation. • Familiarity with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure) is a plus. • Excellent problem-solving skills and ability to translate business problems into analytical solutions. • Effective communication skills to convey complex technical concepts to diverse audiences. • Demonstrated experience in leading data science projects and mentoring junior team members. • Published research, relevant certifications, and contributions to the data science community are advantageous.
Benefits
• Project-based work: Apply your RevOps expertise to various client projects, with engagements lasting multiple months. • Flexible schedule: Maintain a healthy work-life balance with a schedule ranging from 10-40 hours per week. • Continuous learning: Network with other top-tier RevOps professionals.
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