Head of Engineering, Data Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the engineering function at Theta and manage the data science team.

• Establish technical direction and assist the team in overcoming complex delivery challenges.

• Collaborate with clients' technical teams.

• Design dependable execution of thousands of models on cloud infrastructure.

• Partner with client engineering teams to package and deploy models within their environments.

• Ensure the pipeline from raw client files to validated model outputs is reliable and reusable.

• Create AI-assisted workflows for data preparation and modeling.

• Define standards for testing, validation, and dependable deployment.

• Review the team's code and design work.

• Determine what to build, automate, or outsource while maintaining a focus on maintainability.

• Assist data scientists in resolving challenging client delivery issues and directly contribute when engagements overlap.

⛳️ Requirements

• Strong engineering skills and judgment across engineering, data science, and infrastructure.

• Proven experience in building and operating production data or machine learning systems from start to finish at scale on cloud infrastructure.

• GCP experience is preferred; familiarity with AWS, Azure, Databricks, or Snowflake is also relevant.

• Experience in addressing challenges related to data preparation, model execution, and infrastructure, including handling messy input files and slow model runs.

• Capability to critically examine data and outputs, identifying issues that should halt a run.

• Willingness to learn and work within an established R-based production environment.

• Possess a product engineering mindset, balancing reliability, usability, and delivery requirements.

• Ability to guide a small, seasoned data science team through hands-on technical support and resolve complex delivery challenges.

• Comfortable participating in client meetings to explain technical methodologies and trade-offs, discuss data requirements, and understand clients’ technology stacks and infrastructure.

• Genuine interest in developing AI-assisted workflows, with a capacity to quickly learn unfamiliar tools and critically assess outputs.

• Preferred: Experience in building and assessing AI-assisted workflows for data preparation and modeling, including LLM or agent-based systems.

• Preferred: Experience with production R, including packaging, dependency management, containers, or C++ integration via Rcpp.

• Preferred: Background in statistical modeling, particularly familiarity with CLV or BTYD models.

• Preferred: Experience in deploying data or modeling workflows in client-controlled environments, such as Databricks, Snowflake, or Spark.

• Preferred: Experience with infrastructure as code, such as Terraform or similar, and CI/CD practices.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and growth.

• Flexible work hours and remote work options.

• Collaborative and innovative work environment.

• Health and wellness benefits.