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Senior Data Scientist
Job summary
A tech startup that is building a foundational platform for finance automation is seeking a Senior Data Scientist. In this fully remote position, you will architect and build important data infrastructure and AI systems, collaborating closely with the founding team. Ideal candidates will possess deep experience in data architecture and distributed systems, and will have a strong track record in building production-grade solutions. This is an exciting opportunity to join a high-impact team during a pivotal moment for the company.
Benefits
Qualifications
- Deep experience with data architecture and distributed systems.
- Proven ability to build production-grade data and AI systems end to end.
- Strong understanding of scalability, reliability, and performance constraints.
Responsibilities
- Build scalable data pipelines, ETL/ELT processes, and real-time workflows.
- Develop, optimize, and productionize ML/LLM models and pipelines.
- Define best practices for data engineering and AI lifecycle management.
Skills
About Elements Elements is building a foundational platform to automate and connect high-stakes finance workflows. We are in advanced beta, live with early customers, and preparing for a full production launch. The product is already operating in demanding, real-world environments. This is a rare moment to join early with real traction and low execution risk. We are well funded, actively used by multiple customers, and seeing strong inbound demand as we prepare to scale.
We are hiring a Senior Data Scientist to architect and build the data infrastructure, AI pipelines, and intelligent workflow systems that power mission‑critical finance operations. This high‑ownership, fully remote role includes close collaboration with the founders and direct influence on the platform’s intelligence layer.
- Build scalable data pipelines, ETL/ELT processes, and real‑time workflows.
- Architect the data and AI foundation enabling advanced automation.
- Develop, optimize, and productionize ML/LLM models and pipelines.
- Own key components of the data platform as we scale into production.
- Define best practices for data engineering and AI lifecycle management.
- Collaborate cross‑functionally to translate complex finance needs into intelligent systems.
- Deep experience with data architecture and distributed systems.
- Proven ability to build production‑grade data and AI systems end to end.
- Strong understanding of scalability, reliability, and performance constraints.
- Comfortable operating in zero‑to‑one, high‑ambiguity environments.
- Strong technical judgment and ownership mindset.
- Background in B2B SaaS or Fintech is a plus.
- Ownership in a category‑defining platform.
- Meaningful equity as a founding team member.
- Direct impact on modern finance automation and intelligence.
- A senior, engineering‑focused team solving hard problems.
- ...
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.