Staff Data Scientist

Key responsibilities:

• Analyze large datasets from various sources to identify trends, patterns, and actionable insights that help define and execute data-driven strategies
• Design, develop, and deploy statistical models, machine learning algorithms, generative AI models, and predictive analytics to optimize plan recommendation, churn predictions, subscription propensity, winback strategies
• Integrate machine learning models into production systems to deliver real-time insights and automated decision-making capabilities
• Collaborate closely with cross-functional teams, including Data Engineering, Product Management, Growth and Business teams, to understand business challenges and deploy end-to-end solutions
• Continuously evaluate and improve data quality and model performance to ensure consistent, reliable, and accurate insights
• Develop and execute A/B testing frameworks and experimental designs to validate algorithmic improvements and quantify business impact
• Stay up-to-date with the latest advancements in data science, machine learning, and AI, and proactively incorporate cutting-edge techniques into models
• Present findings, methodologies, and business impact of data science initiatives to technical and non-technical stakeholders

Skills and attributes for success:

• Proven experience in data science and machine learning preferably in subscription modeling, revenue modeling or related industries
• Experience building and tuning supervised models (e.g., churn prediction, propensity scoring, offer targeting)
• Strong proficiency in Python, SQL, and relevant data science libraries (Pandas, Scikit-learn, TensorFlow, PyTorch, etc.)
• Expertise in building and deploying machine learning models into production systems
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Google Cloud)
• Deep understanding of statistical analysis, machine learning, data mining, and predictive modeling techniques
• Should be comfortable leveraging LLMs and internals
• Strong product intuition to translate business goals (e.g., reduce churn, boost conversion) into actionable data science solutions with measurable impact
• Strong problem-solving skills with the ability to translate business problems into data science solutions
• Excellent verbal and written communication skills, with the ability to present complex information to non-technical stakeholders

Preferred education and experience:

• Master's or PhD in Computer Science, Statistics, Mathematics, or related quantitative field with 7+ years of experience in applied data science/machine learning