Quant Researcher

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

We are hiring for a Python Developer at Wissen Technology!

📍 Location: Pune (Hybrid)

💼 Experience: 3–6 Years

⏱️ Notice Period: Immediate / 15 days preferred

🔧 Key Skills:

• Strong experience in Python

• Hands-on with Pandas & NumPy

• Experience with AWS (S3, Lambda preferred)

• Good understanding of data processing & APIs

• SQL knowledge

🏢 About Wissen Technology:

Wissen Technology, part of the Wissen Group (est. 2000), is a fast-growing technology company specializing in high-end consulting across Banking, Finance, Telecom, and Healthcare domains.

✔️ Global presence – US, India, UK, Australia, Mexico & Canada

✔️ Certified Great Place to Work®

✔️ Trusted by Fortune 500 clients like Morgan Stanley, Goldman Sachs, and more

✔️ Strong growth with 400% revenue increase in recent years

🌐 Website: www.wissen.com

🔗 LinkedIn: https://www.linkedin.com/company/wissen-technology/

If you’re interested or have relevant candidates, please share your resume at [your email].

#Hiring #PythonDeveloper #PuneJobs #AWS #ImmediateJoiner

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology:

·        The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.

·        Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.

·        Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.

·        Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.

·        Globally present with offices US, India, UK, Australia, Mexico, and Canada.

·        We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.

·        Wissen Technology has been certified as a Great Place to Work®.

·        Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.

·        Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.

·        We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

De

Job Title: Application Development Engineer (Python – Backtesting & Index Platforms)

Role Overview

Key Responsibilities

Engine Development: Design and implement modular, reusable Python components for index construction, rebalancing, and backtesting.

Large-Scale Simulation: Use Pandas, NumPy, and PySpark to run historical calculations across long time horizons and multiple index variants.

Workflow Integration: Integrate engines with orchestrators such as Airflow or Temporal using parameterized, config-driven execution.

Reference Data Consumption: Query and utilize pricing, security master, and corporate action data from Snowflake.

Quality & Reconciliation: Build automated test harnesses to validate outputs, compare against benchmarks, and guarantee reproducibility.

Performance Optimization: Improve runtime efficiency through vectorization, caching, and distributed computing patterns.

Cross-Team Collaboration: Partner with Business, Index Ops, and Platform teams to accelerate research-to-production onboarding.

Required Technical Capabilities

Python Expertise: Strong proficiency in Python application development with emphasis on clean architecture and maintainable design.

Data & Numerical Libraries: Deep experience with Pandas and NumPy; working knowledge of PySpark for distributed workloads.

Financial Computation: Ability to implement portfolio mathematics, weighting algorithms, and time-series transformations.

Config-Driven Systems: Experience building rule-based or metadata-driven processing frameworks.

Database Skills: Strong SQL and experience consuming structured data from Snowflake.

Testing Discipline: Expertise in unit testing, regression testing, and deterministic replay of calculations.

Orchestration Integration: Familiarity with Airflow, Temporal, or similar workflow engines.

Cloud Infrastructure: Solid understanding of AWS ecosystem services (S3, Lambda, IAM) and how they integrate with the Snowflake Data Cloud.

Sr.Data Scientist,Python, AI ML

We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.

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.

Are you looking to work in the cutting edge area of applying data-science to help global customers get a better insight into their health? If so, read on and apply.

Role Name: Senior Data Scientist

Science Team | Full-Time | In-Office | Bangalore

The Role

The Ultrahuman Science Team builds the algorithms behind the Ring, M1 CGM, blood and urine biomarkers, and Performance Lab assessments. We are hiring a Senior Data Scientist to own those algorithms end to end: from the raw sensor signal to a model that is shipped, monitored, and trusted in users' hands.

This is a build role with real scope. In a typical month you will improve a production algorithm, root-cause a metric users are complaining about, and stand up the data pipeline the next model needs. The common thread is ownership: you take a vague question and return a working answer, without waiting to be handed scope.

What You'll Do

·      Own algorithms end to end: sleep staging, activity detection, sensor-derived metrics, and health scores. You frame the problem, build the features, train and evaluate the model, and see it live

·      Ship models, not notebooks: you prove a change on our own cohort before it reaches users, and a model is done only when it runs in production and you can tell how it is behaving

·      Validate against reference standards: design evaluations against gold standards, reference devices, and study ground truth, and know when a result is real and when it is an artifact

·      Own the data layer: cohort extraction, feature pipelines, study data, and raw sensor data, so the next model starts from clean inputs

What This Looks Like in Practice

1. Improving production algorithms - Take an existing production model like sleep staging, root-cause the failure modes against reference data, and ship a fix you can defend with numbers.

2. Building new models - Train an activity classifier on raw sensor data, design the labeled data collection that expands it, and pick the operating point so false positives never erode trust.

3. Proving it before it ships - Run a new steps algorithm against reference-device cohorts, decide with data when it is ready, and monitor how it behaves after rollout.

Who You Are

The two things we can't coach

·      High ownership, end to end: you take a problem from a vague question to a shipped model without waiting to be handed scope, and you can point to something you owned from raw data all the way to production

·      Hungry for more scope: you have outgrown your current role and want problems biggerthan your title, with the technical depth to be trusted with them

Also important

·      You've worked with human health data: wearables, physiological signals, or clinical data.

If your experience is close but not exact, show us why you will ramp fast

·      You've built at a startup: or somewhere small enough that nobody handed you clean data, clear specs, or a mature ML platform

·      You work like it's 2026: coding agents and AI tooling are part of how you build every day, and you can tell which new capabilities are worth adopting

·      You communicate: you can explain a model and its limits to a product manager, an engineer, or a founder, and hold your own with our scientists Core Technical Skills

·      Languages and data: Python and SQL daily, comfortable working in a real codebase

·      Machine learning: PyTorch or TensorFlow, scikit-learn, and gradient boosting, with the judgment to know which the problem needs

·      Advanced machine learning: time series and sequence models, deep learning on continuous physiological signals, and ensembles

·      Statistics and evaluation: hypothesis testing, experiment and A/B design, model evaluation, and error analysis against a reference standard

·      Scale and cloud: Spark or equivalent on large datasets, and AWS, GCP, or Azure

·      Production ML and MLOps: training pipelines, model versioning, deployment, monitoring, and drift detection

·      LLMs and agentic systems: fine-tuning and serving models, building agentic pipelines, and using coding agents to move faster

Experience:

- 4 to 5 years building and shipping machine learning systems. We index on what you have shipped and on trajectory, not the exact number of years; if you are a little earlier but have clearly outgrown your current scope, we want to hear from you.

- Bachelor's or higher in engineering, computer science, statistics, or a related field.

How We Work and Who Thrives Here

- The Science team is small and moves fast, and much of the work has no precedent to copy.

- People do their best work here when they are energized by ambiguity, low on ego, quick to adopt a better idea no matter where it comes from, and comfortable owning something before anyone has told them how. If you need a mature data org, clean labelled datasets, and clear guardrails to thrive, this particular role will not be the right fit, and that is worth knowing up front.

What You'll Gain

·      Ownership of algorithms that hundreds of thousands of people see every morning

·      A dataset most scientists never get to touch: 100M+ nights of sleep and continuous physiological signals at scale

·      Direct collaboration with the engineering, product, and design teams building Ultrahuman

Job Title: C Developers 

Company Name: Chella Software Private Limited

Company Website: https://www.chelsoft.com/

Company details

THE PARTNER OF CHOICE FOR FINANCIAL MARKETS

Our deep domain experience, ultra-high-performance software solutions, and on-time project delivery make us the preferred partner for the financial markets.

Over the last two decades, Chella Software has built deep domain experience in the financial markets and a capability for developing ultra-high-performance software that can handle very high volumes of data with the lowest levels of latency.

We are now preferred partners for a host of Central Banks, Stock Exchanges, Clearing Corporations, Brokerages, and Institutional Investors across 12 countries.

We are a global provider of fintech solutions for central banks, exchanges, central counter parties, and financial market intermediaries. We meet the software needs of customers in India, the  Middle East, Africa, Singapore, and the USA.

Location: Mumbai

Mode of Working: Work from office: 2 rounds - virtual

Days of Working: 5 Days a week

Responsibilities

Job Description:  

• Programming Languages: C Platform: Linux and Windows environment 
• Comfortable with software development on Unix/Linux platforms • Strong debugging skills  
• Ability to work independently and efficiently to meet deadlines. Self-motivated, detail-oriented and organized. 
• Strong analytical skills to diagnose/resolve complex issues • Ability to multi-task and stay organized in a dynamic work environment. 
• Ability to "think outside the box". 
• Highly proficient programming skills [C family] 
• Excellent algorithm-design skills 
• Very good knowledge of database concepts and technology, in particular SQL and relational algebra, and query optimization 

Roles & Responsibilities:  

• Planning, estimation, and design usually done in a group  
• Working closely with end-users (traders) to understand their requirements and needs 
• Working closely with the other members of the MC team to identify and employ strategies and solutions to best support the trading desk  
• Working closely with the rest of the SPG to identify and employ strategies and solutions to best support the needs of the MC team  
• Providing support for the traders on trading and risk infrastructure issues 
• Development and support of our trading, risk management, infrastructural and reporting applications 
• Work with the Lead Technologists to develop and deliver solutions within a timely manner within the scope of the overall business strategy 
• Assisting Application Support with root cause analysis of production incidents 

Interview process

Interview Process

• Round 1: Virtual
• Round 2: Virtual
• Final Discussion: Face-to-face in Mumbai 

Perks:

• Training period: 2 months at Madurai; the training cost, Stay, Travel, Food, etc., will be provided by the company
• Yearly 2 travel to your home town shall be sponcered by the company.

We are a San Francisco-based AI infrastructure company working with leading frontier AI labs to build post-training data and evaluation infrastructure for foundation models. We are hiring a Python Developer to create high-quality datasets, reinforcement learning environments, and benchmarking pipelines used to improve and evaluate state-of-the-art LLMs. This is a remote role with flexible working hours.

Responsibilities

* Create and curate datasets for LLM post-training (SFT, RLHF, RL, preference optimization).

* Build and maintain RL environments for agent evaluation.

* Develop Python tooling for dataset generation, validation, and transformation.

* Evaluate models on custom benchmarks and testing pipelines.

* Collaborate with research and engineering teams to deliver client-specific post-training datasets.

* Work with terminal-first development workflows and cloud infrastructure.

Required Skills

* Strong Python programming skills.

* Understanding of LLM fundamentals and post-training concepts (SFT, RLHF, RL).

* Experience working with structured data (JSON, CSV, YAML).

* Git, Linux/Unix command line, and solid software engineering fundamentals.

Good to Have

Experience with RAG, agentic AI systems, Hugging Face Transformers, LoRA/PEFT, LangChain or LlamaIndex, vector databases (FAISS, Qdrant, Milvus, Pinecone, Weaviate, ChromaDB), Docker, AWS/GCP, FastAPI/Flask, Bash, CLI tooling, model evaluation frameworks, benchmarking, and AI infrastructure.

Compensation

Base Salary: USD $1,250/month

Equity: ESOP/Equity package included.

Performance Bonuses: Up to USD $4,000/month (in addition to base salary).

Location

Remote (Worldwide)

Work Hours

Flexible, remote-first, asynchronous work environment.

How to Apply

Apply here: https://tally.so/r/wLReJG

Please complete the application form and submit the required details. Only shortlisted candidates will be contacted.

About us

MyRico builds personal AI agents for enterprise, the copilots and digital employees that make humans more productive. The MyRico agents sit at the intersection of enterprise memory, high-end security, and an ever-expanding set of capabilities. We're a small team shipping fast, and the product is live with real customers today.

The role

Full-time · Bangalore

You'll own the systems that make an autonomous agent trustworthy in production. This is not just prompt engineering, and it's not model training - it's that and all the engineering layers in between: model steering, memory architecture, orchestration design, latency optimization, deterministic vs non-deterministic systems tradeoff, deployment, and operator tooling.

Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.

What we're looking for

• More than 7 years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.
• Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.
• Python and shell in production settings; comfortable in TypeScript/Node. You write boring, testable code and prefer the standard library to a new dependency.
• Systems taste: append-only logs, idempotent reconciliation, fold-the-events state machines, and read-only debugging surfaces feel like home.
• Evidence discipline: tests before features, claims backed by quoted observations, decisions written down.

Nice to have

• Experience running the combination of multi-tenant and single-tenant / on-prem-style fleets with ability to handle per-customer isolation, upgrade paths, migration compatibility in both setups.
• Security instincts for products that touch highly sensitive data and systems, including things like executives' email, calendars, and messages: least privilege, loopback-only services, secrets that never hit a log.
• You already orchestrate AI coding agents in your own workflow and have opinions about where they break.

How we work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation, your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

We are seeking a Senior Data Science & ML Associate with 4+ years of applied ML experience to build and ship models end-to-end from data prep and feature engineering to training, evaluation, and deployment driving measurable business impact.

Key Responsibilities

• Build, train, and evaluate ML and deep-learning models

• Engineer features and prepare data at scale

• Deploy models and monitor production performance

• Partner with stakeholders to frame problems and metrics

• Communicate results and drive decisions

• Iterate on models from business feedback

Mandatory Skills

• 4+ years applied machine learning

• Strong Python (Pandas, NumPy, scikit-learn)

• Classical ML and deep learning (TensorFlow/PyTorch)

• Solid statistics and experiment design

• SQL and data wrangling at scale

• Model deployment / MLOps exposure

Nice to Have: NLP or computer vision; cloud ML (SageMaker, Azure ML)

🚀 We’re Hiring | Data Scientist 🧠📊

Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!

🔹 Experience: 8+ Years

🔹 Must-Have Skills:

🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization

📍 Location: Pune

💼 Work Mode: Work from Office

If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!

📩 Interested? Kindly text

#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow