Senior Quant Engineer at Paromint Advisory Pvt Ltd · Mumbai, Hyderabad · 2 - 4 years · ₹36L - ₹60L / yr · Profitable · Posted 22 Jan 2025

Lead the development of advanced quantitative trading models and mentor junior engineers.
Minimum Qualification: Bachelor's or Master's degree in any field, provided the course includes Mathematics or Economics as a subject.
Experience: 4+ years of professional experience in any field, with a strong foundation in Mathematics or Economics.
Locations: London, New York, Mumbai, Hyderabad
How to Apply:
- Login to tacoi.paromint.com.
- Navigate to your Profile.
- Copy your wallet public address from the app.
- Include your wallet public address.
- Mention the job code SQE002.
- Attach your resume to the email.
Note: Candidates will be selected for interview based on their hedging ability, especially in options and commodity derivatives on tacoi.paromint.com.

About Paromint Advisory Pvt Ltd
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We are looking for a rigorous, systems-minded quantitative leader to own our core commercial intelligence engine end-to-end. This is not a traditional dashboard-building or BI reporting seat. You will define, build, and encode the mathematical logic, unit-economic models, and predictive forecasting systems that power our product and drive real commercial decisions for our brands.
You will sit at the intersection of finance, data science, and product engineering, turning complex commercial data, messy founder inputs, and predictive models into defensible, automated product logic and AI agent workflows.
Key Accountabilities
1. Proprietary Systems: Growth Forecasts & P&Ls
- Growth Forecasting: Build and own the methodology that takes a brand’s current performance and projects a defensible 12-month forecast, complete with a rigorous assumption set.
- Financial Architecture: Construct brand-level P&Ls directly from the forecast, mapping revenue, COGS, contribution margin, and operating costs.
- Variance & Calibration: Continuously run models against real outcomes, measure errors, track actuals against projections, and explain every variance.
2. Productization & Agentic Workflow Design
- Product Logic: Translate sophisticated financial and statistical models into production-ready product logic so the system calculates and delivers outputs natively.
- AI Agent Specification: Define what data agents compute, what internal data/benchmarks they draw on, and what assertions they are strictly barred from making.
- Human-in-the-Loop Orchestration: Replace manual validation with automated product rules while establishing clear review gates for human sign-off before deliverables ship.
- Data Schemas & Engineering Collaboration: Specify data structures, validation rules, and pipelines across structured commercial inputs, partnering directly with engineering to bring models to life in production.
3. Decision Framing & Commercial Rigor
- Decision-First Modeling: Design every analysis backwards from the specific commercial decision it is meant to change.
- Uncertainty & Stated Confidence: Size uncertainty statistically, state clearly what sparse or self-reported data cannot support, and attach a stated confidence level to every output.
- Benchmark Library Management: Define and version the benchmark repository (category, stage, market) to evaluate brands accurately even when data is sparse.
4. Enablement & Commercial Communication
- Cross-Functional Communication: Present complex numbers, models, and uncertainties to founders and operators with clarity and authority.
- Quantitative Literacy: Raise the analytical bar across the business by teaching teams how to read and interpret model outputs correctly.
- Documentation & Standards: Write airtight documentation and standards for data/finance deliverables so cross-functional delivery teams can execute autonomously.
What This Seat Is Not
- Not a BI/Reporting Seat: Dashboards are merely one downstream output of this work; your primary focus is proprietary modeling and product architecture.
- Not Research Without Action: We judge models by the decisions they actually changed, not academic complexity.
- Not a Data Engineering Seat: You will specify pipelines, schemas, and logic for engineering to build—you won't be maintaining core infrastructure tables yourself.
Ideal Background & Qualifications
Must-Haves
- Experience: 6–8 years in growth, marketing, commercial, or product analytics within DTC, e-commerce, marketplaces, or specialized platforms.
- Proven Track Record: End-to-end ownership of a forecasting, unit-economics, or media-mix model that commercial teams relied on for high-stakes budget or strategic decisions. You can name the decisions your model changed and what followed.
- DTC Unit Economics Mastery: Deep fluency in CAC, AOV, COGS, contribution margin, LTV, payback period, breakeven, retention cohorts, and working capital reconciliation.
- Modelling with Incomplete Data: Demonstrated ability to build robust outputs from banded, self-reported, or partial founder inputs while explicitly quantifying confidence levels.
- Statistical Rigor: Strong foundation in sizing uncertainty, managing sample limitations, and maintaining analytical integrity.
- Technical Depth: Hands-on daily fluency in SQL and Python.
- Product & Engineering Collaboration: Experience working directly with engineering teams to turn quantitative models or metric definitions into production software.
- Communication: Exceptional presence and ability to defend underlying assumptions and model uncertainty under direct challenge.
Nice-to-Haves
- Media mix modeling (MMM), incrementality testing, or causal measurement methodologies.
- Applied machine learning experience (forecasting, propensity, or segmentation models in production).
- Experience evaluating generative AI or multi-agent system outputs.
- Familiarity with modern data stack layers (Snowflake, BigQuery, dbt) and attribution platforms (Triple Whale, Northbeam, Rockerbox).
- Exposure to multi-brand ecosystems via agency, consulting, or platform environments.
- Experience in early-stage product environments where models and products were co-developed from scratch.
As an Engineering Manager, you'll lead efforts to strengthen and optimize our state-of-the-art systems, ensuring high performance, scalability, and efficiency across our suite of trading solutions.
The core responsibilities for the job include the following:
Technical Expertise:
- C++ coding and debugging to strengthen and optimize systems.
- Design and architecture (HLD/LLD) to ensure scalable and robust solutions.
- Implementing and enhancing DevOps, Agile, and CI/CD pipelines to improve development workflows.
- Managing escalations and ensuring high-quality customer outcomes.
Architecture and Design:
- Define and refine the architectural vision and technical roadmap for enterprise software solutions.
- Design scalable, maintainable, and secure systems in line with business goals.
- Collaborate with stakeholders to translate requirements into technical solutions.
- Driving engineering initiatives to foster innovation, efficiency, and excellence.
Project Management:
- Oversee project timelines, deliverables, and quality assurance processes.
- Coordinate cross-functional teams to ensure seamless integration of systems.
- Identify risks and proactively implement mitigation strategies.
Technical Leadership:
- Lead and mentor a team of engineers, fostering a collaborative and high-performance culture.
- Provide technical direction and guidance on complex software engineering challenges.
- Drive code quality, best practices, and standards across the engineering team.
Requirements:
- 10-15 years in the tech industry, with 2-4 years in technical leadership or managerial roles.
- Technical Expertise: Expertise in C++ development, enterprise architecture, and scalable system design, and proficiency in performance optimization, scalability, software architecture, and networking principles.
- Extensive experience managing the full development lifecycle of large-scale software products, from concept to deployment.
- Strong knowledge of STL containers, multi-threading concepts, and algorithms.
- Solid understanding of memory management and efficient resource utilization.
- Microservices Architecture Expertise: Experience in designing and implementing scalable, reliable microservices.
- Strong Communication and Decision-making skills: Ability to clearly articulate trade-offs, make informed decisions, and ensure alignment across stakeholders.
- Commitment to Creating and fostering Engineering Excellence: Deep understanding of best practices, including code quality, testability, security, and release management, and passion for fostering a strong engineering culture and continuously improving developer workflows and tools.
- Self-Driven and Motivated: Ability to operate independently while driving impactful results.
As an Engineering Manager, you'll lead efforts to strengthen and optimize our state-of-the-art systems, ensuring high performance, scalability, and efficiency across our suite of trading solutions.
The core responsibilities for the job include the following:
Technical Expertise:
- C++ coding and debugging to strengthen and optimize systems.
- Design and architecture (HLD/LLD) to ensure scalable and robust solutions.
- Implementing and enhancing DevOps, Agile, and CI/CD pipelines to improve development workflows.
- Managing escalations and ensuring high-quality customer outcomes.
Architecture and Design:
- Define and refine the architectural vision and technical roadmap for enterprise software solutions.
- Design scalable, maintainable, and secure systems in line with business goals.
- Collaborate with stakeholders to translate requirements into technical solutions.
- Driving engineering initiatives to foster innovation, efficiency, and excellence.
Project Management:
- Oversee project timelines, deliverables, and quality assurance processes.
- Coordinate cross-functional teams to ensure seamless integration of systems.
- Identify risks and proactively implement mitigation strategies.
Technical Leadership:
- Lead and mentor a team of engineers, fostering a collaborative and high-performance culture.
- Provide technical direction and guidance on complex software engineering challenges.
- Drive code quality, best practices, and standards across the engineering team.
Requirements:
- 6-13 years in the tech industry, with 2-4 years in technical leadership or managerial roles.
- Technical Expertise: Expertise in C++ development, enterprise architecture, and scalable system design, and proficiency in performance optimization, scalability, software architecture, and networking principles.
- Extensive experience managing the full development lifecycle of large-scale software products, from concept to deployment.
- Strong knowledge of STL containers, multi-threading concepts, and algorithms.
- Solid understanding of memory management and efficient resource utilization.
- Microservices Architecture Expertise: Experience in designing and implementing scalable, reliable microservices.
- Strong Communication and Decision-making skills: Ability to clearly articulate trade-offs, make informed decisions, and ensure alignment across stakeholders.
- Commitment to Creating and fostering Engineering Excellence: Deep understanding of best practices, including code quality, testability, security, and release management, and passion for fostering a strong engineering culture and continuously improving developer workflows and tools.
- Self-Driven and Motivated: Ability to operate independently while driving impactful results.







