What are the responsibilities and job description for the Sr. Data Scientist Lead position at Fynbosys Inc?
Role Overview
We are seeking a highly analytical and strategic Data Science professional to drive insights and decision-making across the QuickBooks Desktop ecosystem. This role focuses on customer growth initiatives including upgrade, attach, monetization, and migration strategies. The ideal candidate will combine strong technical expertise with business acumen to influence product and marketing outcomes.
Key Responsibilities
• Define and frame business problems, develop hypotheses, establish success metrics, and deliver actionable recommendations
• Generate strategic insights to support customer lifecycle initiatives including upgrade, attach, monetization, and migration
• Build predictive models, customer segmentation frameworks, and profiling solutions to drive product and marketing decisions
• Analyze experimentation results (A/B testing) and marketing performance to inform optimization strategies
• Translate complex data findings into clear, actionable insights for both technical and non-technical stakeholders
• Partner with product, marketing, and leadership teams to influence roadmap and strategic direction
• Design and implement scalable analytics solutions and reusable data assets to improve efficiency and consistency
• Build and maintain data pipelines and ETL workflows using SQL, Python, and cloud-based data platforms
• Generate strategic insights to support customer lifecycle initiatives including upgrade, attach, monetization, and migration
• Build predictive models, customer segmentation frameworks, and profiling solutions to drive product and marketing decisions
• Analyze experimentation results (A/B testing) and marketing performance to inform optimization strategies
• Translate complex data findings into clear, actionable insights for both technical and non-technical stakeholders
• Partner with product, marketing, and leadership teams to influence roadmap and strategic direction
• Design and implement scalable analytics solutions and reusable data assets to improve efficiency and consistency
• Build and maintain data pipelines and ETL workflows using SQL, Python, and cloud-based data platforms
Required Qualifications
• 8–10 years of experience in Data Science or Business Analytics
• Strong experience in developing data-driven strategies that drive measurable business impact
• Hands-on experience with experimentation frameworks (A/B testing), marketing analytics, and attribution modeling
• Proficiency in SQL and Python for data analysis, modeling, and ETL development
• Experience working with cloud-based data platforms (e.g., AWS, Google Cloud Platform, Azure)
• Strong data visualization and storytelling skills with the ability to influence senior stakeholders
• Proven ability to generate hypotheses based on customer behavior, market trends, and business context
• Experience building scalable, reusable analytics frameworks and solutions
• Excellent communication and stakeholder management skills
• Ability to operate independently in a fast-paced environment and lead initiatives end-to-end
• Strong experience in developing data-driven strategies that drive measurable business impact
• Hands-on experience with experimentation frameworks (A/B testing), marketing analytics, and attribution modeling
• Proficiency in SQL and Python for data analysis, modeling, and ETL development
• Experience working with cloud-based data platforms (e.g., AWS, Google Cloud Platform, Azure)
• Strong data visualization and storytelling skills with the ability to influence senior stakeholders
• Proven ability to generate hypotheses based on customer behavior, market trends, and business context
• Experience building scalable, reusable analytics frameworks and solutions
• Excellent communication and stakeholder management skills
• Ability to operate independently in a fast-paced environment and lead initiatives end-to-end
Preferred Qualifications
• Experience in fintech, SaaS, or SMB-focused products
• Exposure to customer lifecycle analytics (acquisition, retention, monetization)
• Experience working with product analytics in a platform or ecosystem environment
• Exposure to customer lifecycle analytics (acquisition, retention, monetization)
• Experience working with product analytics in a platform or ecosystem environment
Salary : $70