Head of Engineering, Data Science

Vaga não está no LinkedIn

🕒 Outubro 19

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🔴 Especialista

👮‍♀️ Gerente de Engenharia de Software

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Theta

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2018

💼 Consultoria

📣 Marketing

💸 Finanças

Consulting • Marketing • Finance

A Theta é uma empresa especializada em analytics preditivo de clientes e valuation corporativo. Oferece soluções inovadoras para compreender e prever o comportamento dos clientes por meio de seu avançado modelo de Customer Lifetime Value (CLV), o CLV Ultra. Desenvolvido para empresas de investimento e corporações, o modelo ajuda os clientes a aprimorar suas estratégias de marketing, aumentar o engajamento dos clientes e tomar decisões de negócios mais embasadas, fornecendo insights aprofundados sobre a economia unitária dos clientes e metodologias de valuation corporativo.

Descrição

• Own Theta’s engineering function and lead its data science team • Set technical direction and help the team resolve difficult delivery problems • Work with clients’ technical teams • Architect reliable execution of thousands of models on cloud infrastructure • Work with client engineering teams to package and deploy models in their own environments • Make the pipeline from raw client files to validated model outputs reliable and reusable • Develop AI-assisted workflows for data preparation and modeling • Set standards for testing, validation, and reliable deployment • Review the team’s code and designs • Decide what to build, automate, or outsource while ensuring maintainability • Help data scientists resolve difficult client delivery problems and contribute directly when engagements overlap

🎯 Requisitos

• Deep engineering skills and judgment across engineering, data science, and infrastructure • Experience building and operating production data or ML systems end to end at scale on cloud infrastructure • Experience with GCP preferred; AWS, Azure, Databricks, or Snowflake also relevant • Experience solving problems across data preparation, model execution, and infrastructure, from messy input files to slow model runs • Ability to critically check data and outputs and identify issues that should stop a run • Willingness to learn and work in an existing R-based production stack • Product engineering mindset, balancing reliability, usability, and delivery needs • Ability to lead a small, experienced data science team through hands-on technical guidance and resolve difficult delivery problems • Comfortable participating in client calls to explain technical methods and trade-offs, discuss data requirements, and understand clients’ technology stacks and infrastructure • Genuine interest in developing AI-assisted workflows, ability to learn unfamiliar tools quickly, and critically evaluate outputs • Preferred: Experience building and evaluating AI-assisted workflows for data preparation and modeling, including LLM or agent-based systems • Preferred: Production R experience, including packaging, dependency management, containers, or C++ integration through Rcpp • Preferred: Statistical modeling, especially familiarity with CLV or BTYD models • Preferred: Experience deploying data or modeling workflows in client-controlled environments, including Databricks, Snowflake, or Spark • Preferred: Infrastructure as code experience, such as Terraform or similar, and CI/CD

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