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A quantitative investment firm focused on the Indian markets
About the company
The client is a quantitative investment firm focused on Indian financial markets. They operate a multi-strategy, multi-manager platform designed to generate consistent, risk- adjusted returns.
Their approach combines systematic investment methods, rigorous quantitative research and institutional-grade manager evaluation. We bring together research, technology and data to build scalable investment solutions.
Role Overview
We are seeking a Quantitative Developer with strong C++ and Python expertise to convert mathematical models and research prototypes into reliable, high-performance analytical engines.
You will work closely with Quantitative Research, Data Engineering, AI and Product Engineering teams throughout the full model lifecycle—from research handover and production implementation to validation, deployment and ongoing support.
This role is ideal for someone who enjoys working at the intersection of quantitative finance, numerical computing and production software engineering.
Key Responsibilities
Research Production
- Translate mathematical models and Python research prototypes into robust, production-quality C++.
- Develop reusable components for risk analytics, forecasting, portfolio analysis and simulation.
- Build efficient Python interfaces for C++ components using pybind11 or similar technologies.
- Ensure production implementations remain mathematically and numerically consistent with the underlying research.
- Establish clear and reproducible processes for transitioning models from research to production.
Engine Development and Validation
- Design and develop analytical engines capable of processing historical, batch and streaming data.
- Integrate calculation components with data pipelines, APIs, databases and downstream applications.
- Validate production implementations against research prototypes, benchmark datasets and expected results.
- Develop automated numerical, unit, integration, regression and performance tests.
- Identify and resolve numerical stability, precision and edge-case issues.
- Optimize calculation speed, memory usage, concurrency and scalability.
- Profile and benchmark critical components to meet defined performance requirements.
Deployment and Delivery
- Package analytical engines as libraries, services, APIs or containers.
- Support deployment across internal infrastructure and client-controlled environments.
- Configure engines for different datasets, workflows and institutional requirements.
- Assist with integration testing, production upgrades, issue diagnosis and technical troubleshooting.
- Implement appropriate logging, monitoring and error-handling capabilities.
- Document interfaces, assumptions, configurations, dependencies and deployment requirements.
Collaboration and Ownership
- Work closely with Quantitative Research, Data Engineering, AI and Product Engineering teams.
- Participate in technical design discussions, code reviews and quantitative model reviews.
- Communicate implementation trade-offs, constraints and risks clearly to technical and quantitative stakeholders.
- Take end-to-end ownership of assigned components, from research handover through production deployment and support.
- Contribute to engineering standards, reusable libraries and development best practices.
Required Qualifications
- Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, Quantitative Finance or a related discipline.
- Strong professional programming experience in modern C++, including object- oriented and generic programming.
- Proficiency in Python and scientific-computing libraries such as NumPy, pandas or SciPy.
- Experience translating mathematical or analytical prototypes into production software.
- Strong understanding of algorithms, data structures, software architecture and design principles.
- Experience building automated unit, integration and performance tests.
- Familiarity with numerical methods, floating-point behaviour and numerical validation.
- Experience profiling and optimizing compute-intensive or data-intensive applications.
- Proficiency with Git and modern software-development practices.
- Strong analytical, debugging and problem-solving skills.
- •Ability to work effectively with both researchers and software engineers.
Preferred Qualifications
- Experience with pybind11, Boost.Python, Cython or similar interoperability technologies.
- Knowledge of quantitative finance, portfolio analytics, risk modelling, forecasting or simulation.
- Familiarity with time-series data and financial-market datasets.
- Experience developing applications that process batch or real-time streaming data.
- Exposure to concurrent, parallel or distributed computing.
- Experience with containerization and deployment technologies such as Docker.
- Familiarity with Linux environments, CI/CD pipelines and cloud or on-premises infrastructure.
- Experience building analytical libraries, calculation services or APIs for institutional users.
- Knowledge of Indian financial markets is advantageous
About Us
Dolat Capital is a multi-strategy quantitative trading firm specializing in high-frequency and fully automated trading systems across global markets. We build proprietary algorithms using advanced mathematical, statistical, and computational techniques.
We are looking for an Experienced Quantitative Researcher to develop, test, and optimize quantitative trading strategies—primarily for APAC markets. The ideal candidate brings strong mathematical thinking, hands-on trading experience, and a track record of building profitable models.
Key Responsibilities
- Research, design & develop quantitative trading strategies
- Analyse large datasets and build predictive models / regression models
- Implement models in Python / C++ / Matlab
- Monitor, execute, and improve existing trading strategies
- Collaborate closely with traders, developers, and researchers
- Optimize trading systems, reduce latency, and enhance execution
- Identify new trading opportunities across listed products
- Oversee and manage risk for options, equities, futures, and other instruments
Required Skills & Experience
- Minimum 3+ years experience on a high-volume equities, futures, options, or market-making desk
- Strong background in Statistics, Mathematics, Physics, or related field (PhD)
- Proven track record of profitable real-world trading strategies
- Strong programming experience: C++, Python, R, Matlab
- Experience with automated trading systems and exchange protocols
- Ability to work in a fast-paced, high-pressure trading environment
- Excellent analytical skills, precision, and attention to detail
Type: Client-Facing Technical Architecture, Infrastructure Solutioning & Domain Consulting (India + International Markets)
Role Overview
Tradelab is seeking a senior Solution Architect who can interact with both Indian and international clients (Dubai, Singapore, London, US), helping them understand our trading systems, OMS/RMS/CMS stack, HFT platforms, feed systems, and Matching Engine. The architect will design scalable, secure, and ultra-low-latency deployments tailored to global forex markets, brokers, prop firms, liquidity providers, and market makers.
Key Responsibilities
1. Client Engagement (India + International Markets)
- Engage with brokers, prop trading firms, liquidity providers, and financial institutions across India, Dubai, Singapore, and global hubs.
- Explain Tradelab’s capabilities, architecture, and deployment options.
- Understand region-specific latency expectations, connectivity options, and regulatory constraints.
2. Requirement Gathering & Solutioning
- Capture client needs, throughput, order concurrency, tick volumes, and market data handling.
- Assess infra readiness (cloud/on-prem/colo).
- Propose architecture aligned with forex markets.
3. Global Architecture & Deployment Design
- Design multi-region infrastructure using AWS/Azure/GCP.
- Architect low-latency routing between India–Singapore–Dubai.
- Support deployments in DCs like Equinix SG1/DX1.
4. Networking & Security Architecture
- Architect multicast/unicast feeds, VPNs, IPSec tunnels, BGP routes.
- Implement network hardening, segmentation, WAF/firewall rules.
5. DevOps, Cloud Engineering & Scalability
- Build CI/CD pipelines, Kubernetes autoscaling, cost-optimized AWS multi-region deployments.
- Design global failover models.
6. BFSI & Trading Domain Expertise
- Indian broking, international forex, LP aggregation, HFT.
- OMS/RMS, risk engines, LP connectivity, and matching engines.
7. Latency, Performance & Capacity Planning
- Benchmark and optimize cross-region latency.
- Tune performance for high tick volumes and volatility bursts.
8. Documentation & Consulting
- Prepare HLDs, LLDs, SOWs, cost sheets, and deployment of playbooks.
- Required Skills
- AWS: EC2, VPC, EKS, NLB, MSK/Kafka, IAM, Global Accelerator.
- DevOps: Kubernetes, Docker, Helm, Terraform.
- Networking: IPSec, GRE, VPN, BGP, multicast (PIM/IGMP).
- Message buses: Kafka, RabbitMQ, Redis Streams.
Domain Skills
- Deep Broking Domain Understanding.
- Indian broking + global forex/CFD.
- FIX protocol, LP integration, market data feeds.
- Regulations: SEBI, DFSA, MAS, ESMA.
Soft Skills
- Excellent communication and client-facing ability.
- Strong presales and solutioning mindset.
- Preferred Qualifications
- B.Tech/BE/M.Tech in CS or equivalent.
- AWS Architect Professional, CCNP, CKA.
Why Join Us?
- Experience in colocation/global trading infra.
- Work with a team that expects and delivers excellence.
- A culture where risk-taking is rewarded, and complacency is not.
- Limitless opportunities for growth—if you can handle the pace.
- A place where learning is currency, and outperformance is the only metric that matters.
- The opportunity to build systems that move markets, execute trades in microseconds, and redefine fintech.
This isn’t just a job—it’s a proving ground. Ready to take the leap? Apply now.


