Quantitative Research & Performance Analytics Engineer

Job description

If you are a quant-minded finance professional who thrives on building robust models, clean data pipelines, and institutional-grade performance reporting, this role is for you.

As Quantitative Research & Performance Analytics Engineer, you will own Allocator One’s private markets performance modelling—designing the engines behind DPI, IRR, PME, and carry/waterfall analytics.

You will partner closely with our Vienna and London teams to automate fund performance reporting and elevate decision quality.

Note: This is a fully remote position based in India; you will work directly with our global teams.

About Allocator One:

Allocator One operates a unique fund model designed to invest in the most promising first-time fund managers worldwide while optimizing fees.

We serve as the anchor investor of choice for exceptional emerging managers, providing unrivalled access, expertise, and operational support.

Within twelve months of launch, we received 1000+ applications, reflecting our commitment to nurturing new talent.

Beyond investing, we act as a co-builder, integrating managers into our Allocator One program—often described as the “Y Combinator for capital allocators”—with essential support in regulation, administration, and structuring.

Our regulated entities in the US, UK, Austria, Germany, India and (soon) Singapore (Allocator One Management GmbH) enable institutional-grade governance and reporting.

Our founding partners:

• Felix Staeritz – Founder of FoundersLane (corporate venture builder), active VC/PE investor; board/advisory roles including the World Economic Forum (WEF) and Fraunhofer.


• Michael Ströck – Entrepreneur with multiple exits, Y Combinator alumnus, investor instrumental in establishing three VC funds; part of a third-generation family business.

Tasks

1.

Performance modelling & reporting

• Own the cash-flow based performance stack: DPI, TVPI, IRR, PME (KS/LN/Direct Alpha), MoM, with and without subscription facilities.


• Build reproducible Python/SQL pipelines that produce ILPA-compliant performance templates and GIPS composites.


• Implement quarterly fund valuations aligned with IPEV; design carried-interest and fee waterfall models.

2.

Scenario analysis & benchmarking

• Run forward-looking simulations for pacing, exit timing, and financing line impacts on performance.


• Develop peer benchmarking and attribution tools to compare portfolio returns vs public and private indices.

3.

Data pipelines & automation

• Maintain canonical cash-flow ledgers (contributions, distributions, fees, NAVs).


• Partner with engineering to automate ingestion, reconciliation, and reporting pipelines; reduce time-to-insight.


• Build transparent audit trails that stand up to institutional LPs and regulators.

4.

Collaboration within Allocator One

• Work directly with fund finance, investor relations, and the founding team to align modelling with investor needs.


• Translate technical results into actionable insights for boards, founders, and LPs.

Requirements

• Degree in finance, mathematics, statistics, computer science, or related field.


• 3–6 years’ experience in quantitative research, fund analytics, or valuation in private markets.


• Strong technical toolkit: Python (pandas/numpy), SQL, advanced Excel; reproducible coding practices.


• Mastery of IRR quirks (non-periodic flows, negative IRRs) and PME variants.


• Familiarity with ILPA templates, GIPS standards, and IPEV valuation guidelines.


• Excellent written communication; ability to explain quant insights clearly.

Benefits

Culture and how we work:

• Co-builder mindset: We operate as a partner to emerging managers and to each other—hands-on, pragmatic, outcome-driven (“Y Combinator for capital allocators”).


• High standards, low ego: Direct feedback, clear ownership, and high agency.


• Automate by default: We build internal tooling and automate processes with our proprietary Allocator One software.


• Learning loop: Structured onboarding, regular feedback, and access to experienced colleagues.


• Remote-first: Fully remote from India, with deep integration into our Vienna and London teams.

Benefits:

• Competitive base salary with performance bonus


• Low-ego culture with high ownership and autonomy


• Flexible, trust-based working hours; remote by default


• Structured onboarding, dedicated points of contact, and tailored learning opportunities


• Top-tier IT equipment provided

Compensation:

We benchmark competitively against VC/PE and quant hedge fund talent in India.

For mid-level candidates (3–6 years experience), typical base salary ranges are:

• Bangalore / Delhi NCR: ₹20L – ₹40L


• Mumbai: ₹25L – ₹45L

Exceptional candidates with strong quant/hedge fund backgrounds may command higher base packages, reflecting the upper quartile of the market.

In addition to base, we offer a performance-linked bonus.

Application process

1. Initial conversation (video): experience/fit and role expectations


2. Technical interview with take-home modelling case (cashflow, PME, ILPA template)


3. Interview with founding partners


4. Final decision

Emerging VC funds often demonstrate superior market performance compared to established VC funds.

Despite the proven outperformance of their funds, first-time fund managers typically struggle to get their funds off the ground.

We understand the challenges and the potential of these young VC funds and their emerging fund managers.

That’s why Allocator One, founded by Felix Staeritz & Michael Ströck, is dedicated to providing emerging fund managers with everything they need to succeed.

Required Skill Profession

Mathematical Science Occupations