Analytics Lead

Who We Are

Tractable is a cutting-edge Artificial Intelligence company transforming visual assessments with Applied AI solutions. Our AI-powered tools are trained on millions of data points, seamlessly connecting all stakeholders involved in insurance, repairs, and sales of homes and cars. We expedite processes, enhance efficiency, and minimize waste, revolutionizing the industry's approach to damage assessment, claims, and repairs.

Founded in 2014, Tractable is the go-to AI solution for top-tier insurance and automotive companies. Our technologies unlock the full potential of Applied AI, making recovery processes up to ten times faster, even in the face of natural disasters like floods and hurricanes.

With a world-class culture and a diverse team representing over 40 nationalities, Tractable stands out as a global employer of choice. We emphasize collaboration, transparency, autonomy, and continuous learning, empowering each team member to make a tangible impact and grow within the organization.

About the Analytics Team

The Analytics team at Tractable is pivotal, supporting crucial products and processes both internally and externally. This team designs, builds, and evolves core data models, driving customer-facing reporting, billing, and AI research and development. Our vision is to enable Tractable and its clients to make high-value decisions confidently and promptly.

Belonging to the larger Engineering group - Dev Foundations - the Analytics team collaborates with peer teams, product managers, and researchers to ensure the provision of timely, accurate, and reliable data essential for swift product development.

Role and Responsibilities

As the Analytics Lead, you will advance our Analytics capability to a world-class level, influencing technical direction and championing best practices. You will focus on enhancing the user experience for Tractable's customers, researchers, data scientists, and product engineers. Your responsibilities include:

• Gaining an in-depth understanding of Tractable’s products and optimizing data models accordingly
• Leading and mentoring a diverse team of Analysts
• Collaborating with Product and Engineering leaders to integrate customer-facing analytics seamlessly
• Enabling rapid, automated ML model evolution with Research and Engineering teams
• Driving clarity and action through data and analytics with other internal teams
• Ensuring high-level security and governance of analytical data and systems
• Championing cost-efficiency and data pipeline performance
• Maintaining a comprehensive data catalogue for easy discovery and understanding
• Promoting a culture of data self-service and enablement
• Providing clear direction and managing priorities for the team

Tech Stack

We utilize a variety of tools and technologies and are open to exploring new ones as needed. Experience with all listed tools isn’t required; a willingness to innovate and solve problems is more important. Our current stack includes:

• Data stack: AWS MSK, AWS Lambda, AWS Redshift, dbt, Airflow, Airbyte, AWS Glue, Streamlit, AWS Quicksight, Tableau
• Databases: Postgres / RDS, Redis, DynamoDB
• Languages: Python, SQL (Redshift, Postgres)
• IAC & CI/CD: Terraform, CDK, Docker, Harness

We encourage applications from diverse backgrounds as we value a strong culture match and growth potential over existing tool familiarity.

What Will Make You Successful

A successful candidate will be passionate about clarity in data and possess strong software engineering principles. Specific qualifications include:

• Excellent communication skills, able to distill complex situations into clear actions
• Ability to drive process and technical change independently
• 5+ years in data modeling and insight design
• Experience in building and maintaining data pipelines, ideally with dbt
• Proficiency with modern data infrastructure, such as Redshift, BigQuery, Snowflake
• Experience with externally facing dashboards and data integrations
• Strong data governance practices
• Customer-focused approach to data product development
• Leadership and mentoring experience
• Professional experience with Python and software engineering principles in data products
• Experience in managing infrastructure via Terraform or AWS CDK