At a Glance
- Tasks: Architect data foundations and automation workflows for a leading deep tech venture capital firm.
- Company: Join a $1bn AUM deep tech venture capital firm with a diverse portfolio.
- Benefits: Competitive salary, high autonomy, and direct access to partners.
- Other info: Work in a dynamic environment with sector experts in cutting-edge fields.
- Why this job: Be the sole architect of innovative data products that shape the future of investment.
- Qualifications: 2-4 years in data or ML engineering, proficient in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
Deep tech venture capital firm with $1bn AUM and a portfolio of 60+ IP-rich companies across AI, quantum, and biotech.
You will serve as the sole architect of the firm's data foundations and automation workflows. This high-autonomy role bridges the investment and platform teams, empowering you to build proprietary data products and deploy pragmatic AI/ML solutions that directly influence deal sourcing, portfolio monitoring, and fund operations at a premier European venture fund.
Location: London, UK
Why this role is remarkable:
- Rare opportunity to join a technical investment team of 18 as a 'team of one,' with direct access to partners and no bureaucratic silos.
- Full ownership of the firm's technical edge, building the core data and AI infrastructure from the ground up rather than performing one-off analyses.
- Deep immersion in the frontier tech ecosystem, working alongside sector experts and founders in high-impact fields like semiconductors and biotech.
What You Will Do:
- Design and scale the firm's data foundations, including sophisticated modeling, enrichment, and governance for internal and external data sources.
- Deploy pragmatic AI/ML systems such as LLM-enabled research tools and automated document analysis to drive organizational leverage.
- Develop proprietary data products that provide a competitive advantage in market mapping, investment diligence, and portfolio reporting.
The ideal candidate:
- 2-4 years of professional experience in data or ML engineering with a proven track record of shipping and owning production systems.
- High proficiency in Python and SQL with the ability to build end-to-end data solutions from ingestion to user-facing applications.
- Commercially minded problem-solver who can translate ambiguous strategic needs into durable technical systems within a high-judgment environment.
Product + Automation Engineer at $1bn AUM deep tech venture capital firm employer: Jack & Jill
Join a pioneering deep tech venture capital firm in London, where you will have the unique opportunity to shape the future of data and automation within a high-autonomy environment. With a focus on innovation and collaboration, this role offers direct access to partners and the chance to work alongside industry experts in cutting-edge fields like AI and biotech, fostering both personal and professional growth. Enjoy a dynamic work culture that values creativity and initiative, making it an ideal place for those seeking meaningful and impactful employment.
StudySmarter Expert Advice🤫
We think this is how you could land Product + Automation Engineer at $1bn AUM deep tech venture capital firm
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Product + Automation Engineer at $1bn AUM deep tech venture capital firm
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Jack & Jill, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jack & Jill. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Jack & Jill
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jack & Jill!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
