Job Specifications
Company Description
At TwoWay, we’re building category-defining software for global investment banks — and doing it with a team that values speed, ownership, and real impact. If you’re sharp, driven, and thrive in fast-paced, high-stakes environments, you’ll feel right at home.
We’re a small, tight-knit team where:
Ideas move fast
Talent is trusted
Execution beats hierarchy
We believe in clarity over fluff, shipping over perfection, and impact over ego.
TwoWay is a hybrid company with teammates across France and Europe. Our HQ is at Station F in Paris, the world’s largest startup campus and home to a thriving tech ecosystem.
Role Description
We’re hiring our first Head of Data/AI to build and lead the data function at TwoWay.
You will report directly to our CTO, work closely with our CEO and COO, and own the strategy and execution of everything related to data: from ingestion and storage to analytics, ML/LLM pipelines, and trader-facing features. Think “founding data leader” rather than “reporting layer in a big org”.
This is a high-leverage, hands-on role: you’ll define the roadmap, build the first versions yourself, then hire and mentor a small, senior team around you (data engineering, ML, analytics).
As our Head of Data, you will:
Own the data vision and strategy
Design and evangelize a clear data strategy aligned with our product and commercial roadmap (parsing chats, pricing workflows, trader copilots, risk, reporting).
Define what “great” looks like for data at TwoWay: architecture, quality standards, SLAs, metrics, data contracts, and governance.
Build the data platform
Architect and implement our core data platform: ingestion, storage, modeling, orchestration, and observability.
Choose and integrate the right tools (warehouse/lakehouse, streaming, orchestration, ML stack) with a bias for simplicity, robustness, and cost efficiency.
Implement strong data quality, lineage, and monitoring so we can trust our data in high-stakes environments.
Lead ML, LLM & analytics initiatives
Work closely with engineering and product to turn raw trading data and chats into reliable signals: intent, pricing hints, risk flags, and more.
Own the lifecycle of models (NLP, LLMs, ranking, anomaly detection, forecasting): problem framing, experimentation, deployment, monitoring, and iteration in production.
Partner with GTM and customer teams to deliver clear analytics: desk performance, usage analytics, A/B experiment results, and ROI.
Be hands-on and ship
Write production-grade code (primarily Python + SQL; TypeScript appreciation welcome).
Build first versions quickly, iterate with real traders & users, and only then harden and scale.
Contribute to core engineering practices: CI/CD, testing, observability, security, and compliance (we work with regulated institutions).
Build and lead the team
Plan hiring for the data function (data engineers, ML engineers, analytics) and help us sequence roles sensibly over time.
Set up ways of working: rituals, documentation standards, code review norms, collaboration with product & engineering.
Mentor and unblock people — while still staying close enough to the code and data to be credible.
Qualifications
You don’t have to tick every box, but you should recognize yourself in most of these:
Background & experience
7–10+ years of experience across data engineering / data science / ML, with several years owning production systems.
2–4+ years in a lead / head-of / principal role where you shaped data strategy and led others (formally or informally).
Experience building or re-architecting a data platform from scratch at a startup or scale-up (ideally B2B SaaS or fintech / financial services).
Technical skills
Strong hands-on skills in Python and SQL, including building data pipelines and services.
Deep understanding of modern data architectures (warehouse / lakehouse, streaming vs batch, event-driven systems).
Familiarity with orchestration & transformation tools (e.g. Airflow, Dagster, dbt or similar).
Experience with ML/LLM in production: feature pipelines, deployment, monitoring, and iteration, not just notebooks.
Solid grasp of security, privacy, and compliance constraints when dealing with sensitive or regulated data.
How you work
Hands-on by default – you’re happy to open the editor, design schemas, debug pipelines, and read logs.
Product-minded – you start from user problems (traders, sales, risk, ops), not from technologies.
Systems thinker – you can go from architecture diagrams to concrete migration plans and back again.
Pragmatic – you know where to invest in elegance and where a scrappy solution is enough for now.
Clear communicator – you can explain trade-offs to non-technical stakeholders and align people around a plan.
Nice to have
Experience with trading, market data, or capital markets, especially FX / rates.
Prior work with NLP on chats, LLM-based copilots, or human-in-the-loop labeling pipelines.
Based in Europe / UK and comfortable wo