We are looking for a Technical Chief of Staff – Product & Data to support product execution, data sourcing, and operational alignment across BIT Capital’s research and investment technology stack.
In this role, you will be Chief of Staff to the Chief AI Officer and act as a connector between investment analysts, quantitative researchers and engineering teams. The focus is strongly operational and execution-oriented: ensuring that the right data is sourced, the right problems are clearly specified, and complex cross-team work is executed reliably and with clarity.
This role is focused on execution, clarity, and operational leverage rather than owning a traditional product roadmap. You will operate at the functional level — translating investment and research needs into clear requirements, coordinating stakeholders, and ensuring follow-through in a highly data-driven environment.
Location: Berlin HQ (hybrid)
Relocation: Berlin relocation required (visa/relocation support available)
Discover and evaluate fundamental and alternative datasets together with investment analysts and portfolio managers
Own relationships with data vendors: onboarding, regular check-ins, awareness of schema changes, and renewals (in coordination with legal/compliance)
Maintain a structured overview of datasets, vendors, refresh frequencies, and dependencies
Coordinate dataset evaluations with Quantitative Research and Engineering, covering data quality, feasibility, and operational complexity
Identify and scope self-harvested data opportunities, including web scraping, together with investment analysts and engineers
Translate investment and product intent into clear functional requirements and acceptance criteria for Engineering
Ensure expectations around data freshness, reliability, and failure handling are explicit and understood
Act as a structured interface between investment analysts and technology teams, gathering feedback on workflows, usability, and data trust
Measure and track the impact and adoption of new products and features, using analyst feedback and usage signals
Reduce ambiguity across stakeholders and help Engineering focus on the highest-impact problems
Support documentation, auditability, and governance requirements in collaboration with Engineering and Compliance
3–6 years of experience in a role close to investment research, data, analytics, or product execution
Prior exposure to investing, financial markets, or investment research
Experience working with external data vendors, alternative data, or data-heavy products
Comfort with SQL or Python for lightweight checks or exploration
Strong curiosity about data, including a habit of understanding where raw data comes from and how value is created along the data value chain
Ability to write clear, structured functional specifications and define acceptance criteria
Comfortable collaborating with engineering and data science teams, without needing to design systems yourself
Clear, structured thinking, and exceptional written communication and organizational skills
Comfortable operating in an ambiguous, fast-moving environment
Experience in the investment, financial data, or alternative data ecosystem
Familiarity with modern data platforms (e.g. Databricks, Snowflake, cloud-based data stacks)
Solid foundation on statistics, data modeling and backtesting
Experience with LLM workflows and agentic solutions
Advanced user of AI solutions (AI coding, skills, MCPs, etc.)
Work with large-scale data and modern AI-driven research workflows
Close collaboration with senior leadership and experienced engineers
Flat hierarchy, high responsibility, and a steep learning curve
Competitive compensation, relocation, and visa support
How to apply for this position
Please include your resume and a short note describing:
A data- or research-heavy initiative you worked on
How you coordinated between domain experts and technical teams
What attracted you to this role and to investing
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