Data Scientist, Clio

• We aren’t looking for just any traditional Data Scientist to join this team. We’re looking for someone who takes data seriously, thrives in a rapid-growth, high-velocity environment, and lives and breathes our values. We’re looking for an innovator and a thought leader! We’re looking for someone who is:
• Passionate about driving growth empirically
• Always looking to innovate with data and explore open-ended questions
• A strong partner to business and product stakeholders, with an ability to influence decision-making
• Strategically minded and never shies away from a challenge
• Self-motivated and able to work autonomously and collaboratively
• Agile and responsive, and comfortable with constant change
• 3+ years applied experience in data science
• The ability to translate business requirements into data science solutions
• A proven ability to deliver actionable insights in a fast-paced, iterative environment
• Experience in developing analysis in Python and experience with relevant ML libraries and frameworks (e.g., pandas, PyTorch, scikit-learn)
• Strong team player mindset, while able to work under your own initiative and prioritize time and tasks effectively
• Excellent written and verbal communication skills, with the ability to tell a compelling story with data to both technical and non-technical audiences
• Ability to write structured SQL queries for answering questions and manipulating data
• Demonstrate a keen interest in improving your craft by using AI

Desirable

• You will help lay the foundation for this work by ensuring good data quality, data governance, and analytical practices. And you will also be part of our larger Data & AI team for learning, career development, and company-wide data initiatives
• Suggest and proactively pursue new questions about our business, product, and customers that lead to high-impact insights
• Work with other team members to develop predictive AI and ML solutions and deploy them in production
• Apply rigorous statistical analysis and data mining techniques to evaluate and clearly communicate the impact of different product features and other business initiatives
• Employ statistical analysis, machine learning, GenAI, LLMs, etc. to unlock new product opportunities
• Collaborate closely with product, marketing, and business teams to refine business problems, develop clear hypotheses, and provide data-driven recommendations that shape strategy
• Support scientific thinking in product and business teams by enabling discussions with data, disseminating best practices, and leading by example
• Effectively communicate and present complex technical concepts and findings to diverse stakeholders, ensuring insights are understood and acted upon