Product Data Scientist II 18O25

The role of a Product Data Scientist II is pivotal within any data-driven organization that focuses on product development and optimization. As a Product Data Scientist II, you will leverage your expertise in statistical analysis and data science methodologies to uncover valuable insights from complex datasets. You will work closely with product managers, engineers, and other stakeholders to ensure data-driven decision-making that is aligned with business goals. In this intermediate role, you will be responsible for conducting exploratory data analysis, building predictive models, and designing experiments to test hypotheses about user behavior and product usage. Your ability to communicate data-driven insights and strategies to non-technical team members will help drive product improvements and innovation.

Responsibilities

• Analyze large datasets to extract actionable insights and support product decisions.
• Collaborate with product managers and developers to design data-driven solutions.
• Create predictive models to forecast product trends and user behaviors effectively.
• Design and implement A/B tests to evaluate features and determine impact on KPIs.
• Develop dashboards and reports that visualize key metrics and product performance.
• Analyze user feedback and behavior data to pinpoint areas for product improvement.
• Identify data collection opportunities to enhance overall data quality and relevance.
• Communicate complex analytical results to non-technical stakeholders for informed decisions.
• Collaborate with data engineering teams to develop scalable data pipelines.
• Stay up-to-date with the latest data science tools, techniques, and trends.
• Ensure data and analytics practices comply with regulatory and privacy requirements.
• Mentor junior data scientists by providing guidance and sharing best practices.

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, or a related field.
• A minimum of 2-4 years of experience in data science or analytics roles.
• Proficiency in statistical programming languages such as Python or R is required.
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Strong experience with SQL for data extraction and manipulation from databases.
• Knowledge of machine learning techniques and the ability to apply them effectively.
• Excellent problem-solving skills with a strong attention to detail essential.
• Ability to work collaboratively in a team environment and manage multiple projects.
• Excellent communication skills for conveying analytical concepts to non-technical audiences.
• Familiarity with product development lifecycle and agile methodologies is a plus.