Senior VC Research Analyst

Arcanis
Birmingham
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Backend Engineer (Python) - 6 month contract

SENIOR DATA SCIENTIST - Computer Vision / Generative AI HYBRID

Senior Go Developer

Senior Software Engineer

Senior Azure Cloud Engineer

Senior Software Engineer (Frontend)

About Arcanis:

Arcanis is a research and investment firm focused on deep state-of-the-art data collection and complete insight research automation for Growth and Late-Stage VC.

We replace intuition and gut feeling with provable science through VC full-cycle investment process powered by our proprietary tools and our up-to-date database of Growth and Late Stage companies:

  • Deep Research:a standardized, scalable methodology for VC company research, utilizing state-of-the-art automation from the initial deal draft to expert-level insights ready for Investment Committee review portfolios/strategies for Asset Managers, large LPs, and small and medium VC funds with actionable improvement
  • Systematic Strategies:development of GLS VC strategies with long-term advisory support, offered in a white-label or revenue-sharing model
  • Benchmarking and Monitoring: real-time, actionable performance evaluations and risk assessments, enabling asset managers, LPs, and VC funds to track and optimize their portfolios effectively.

As a relatively young company with a technology-first approach, we've already achieved strong results based on feedback from both current and prospective clients. Although our initial clients are primarily based in Geneva and occupy much of our current capacity, we have a clear automation roadmap that will enable us to scale globally once our solution is stabilized.


Position Overview:

TheSenior Analystat Arcanis plays a crucial role in connecting data experiments, developing new methodologies, automating them with the IT team, and standardizing research processes. Additionally, the Senior Analyst will build the research team’s capacity to meet growing demand.

We are looking for a mature, systematic thinker who is fast on their feet, creative yet grounded in common sense, and with a good sense of humor.A strong background in mathematicsis essential to avoid feeling overwhelmed by complex analytical concepts like Fourier functions or statistical modeling.

The ideal candidate will be able to assemble complex yet robust analytics mechanisms from simple, understandable components. Experience with data and software engineering is necessary to grasp key concepts required for enterprise-level solutions.

A solid understanding of venture capital markets is highly preferred, and experience with enterprise-level LLMs is also required. The role involves leading and organizing the research team, directly reporting to the managing partner, and regularly interacting with internal stakeholders.


Qualifications:

  • 5+ years of experience infinancial analysiswithin later-stage venture capital or private equity.
  • Bachelor’s degree or higher inMathematics, Cybernetics, Data Science, or a related field.
  • Strong leadership and team management skills, with a proven ability to foster collaborative, high-performing teams.
  • Proficiency in data analysis tools (Excel, Python, SQL); experience with AI-driven research methodologies is a significant plus.
  • Deep understanding of venture capital research and decision-making processes.
  • Excellent communication skills, both written and verbal, with the ability to present complex data and insights.
  • Fluency in English is required.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.