- Company Name
- TwoWay
- Job Title
- Head of Data/AI
- Job Description
-
Job title: Head of Data / AI
Role Summary:
Founding data leader responsible for building, scaling, and owning the end‑to‑end data function. Define strategy, architecture, and product‑aligned analytics, ML/LLM pipelines, and data quality systems. Hands‑on engineering, code delivery, and team leadership in a fast‑moving fintech environment.
Expectations:
- 7–10+ years in data engineering, data science, or ML with proven production experience.
- 2–4+ years in a senior or lead role shaping data strategy and mentoring a small team.
- Prior experience designing or rebuilding a data platform for a startup or scale‑up (B2B SaaS, fintech, or financial services).
- Demonstrated ability to ship code (Python + SQL), build pipelines, and iterate quickly with end‑users.
- Strong command of data governance, security, privacy, and compliance for regulated activities.
Key Responsibilities:
**Strategic Leadership**
- Own data vision, strategy, architecture, SLAs, metrics, and governance.
- Align data initiatives with product and commercial roadmaps (chat analytics, pricing workflows, trader copilots, risk, reporting).
**Data Platform Architecture**
- Design and implement core ingestion, storage, modeling, orchestration, and observability.
- Select and integrate warehouses/lakehouses, streaming, orchestration, and ML stacks focused on simplicity, robustness, and cost.
- Implement data quality, lineage, and monitoring frameworks.
**ML/LLM & Analytics**
- Define and manage model lifecycle (feature pipelines, training, deployment, monitoring).
- Deliver robust signals from trading data (intent, pricing, risk) and analytics (desk performance, usage, A/B results).
**Hands‑On Engineering**
- Write production‑grade code (primarily Python + SQL; TypeScript welcome).
- Contribute to CI/CD, testing, observability, security, and compliance.
**Team Build & Operation**
- Plan hiring and growth for data engineers, ML engineers, and analysts.
- Establish rituals, documentation standards, code review norms, and cross‑functional collaboration.
- Mentor and unblock team members while remaining a credible technical leader.
Required Skills:
- **Programming & Data Engineering** – Python, SQL, pipeline development, debugging.
- **Orchestration & Transformation** – Airflow, Dagster, dbt or equivalent.
- **Data Architecture** – Warehouses / lakehouses, batch & streaming, event‑driven systems.
- **ML / LLM Production** – Feature engineering, model training, deployment, monitoring, experimentation.
- **Data Governance** – Data quality, lineage, SLAs, contracts, compliance, and privacy best practices.
- **Cross‑Functional Communication** – Translate technical trade‑offs to non‑technical stakeholders; product‑centric mindset.
- **Leadership** – Team hiring, mentorship, setting working practices, and fostering collaboration.
Required Education & Certifications:
- Bachelor’s or Master’s in Computer Science, Data Engineering, Data Science, or related field.
- Optional professional certifications (e.g., Google Cloud Professional Data Engineer, AWS Big Data Analytics, or similar) are a plus.