Open to opportunities

Ankan Kar

@ankankar

Message

I am a quant-focused software engineer specializing in causal inference, time-series modeling, and algorithmic trading.

India

Message

What I'm looking for

I seek research-driven roles combining causal inference, time-series modeling, and algorithmic trading, with strong MLOps practices, reproducibility, and impact.

I am a software engineer and researcher with a Master of Science in Computer Science and a strong foundation in mathematics. My work focuses on causal inference, changepoint detection, and predictive modeling for both batch and time-series data.

I have built and deployed algorithms on personal GPU servers for backtesting, designed advanced feature-engineering pipelines for financial time series, and developed backend systems for simulating and backtesting trading strategies. In algorithmic trading work I helped achieve a 34% annual return with a -11.20% max drawdown and a 5.24 Sharpe ratio.

My research experience includes generating synthetic datasets for causal model evaluation, constructing causal models from observational data, and publishing in peer-reviewed venues. I contribute to open-source repositories and have practical experience with DoWhy, TensorFlow, PyTorch, and MLOps tooling like MLflow.

I seek roles where I can apply rigorous quantitative methods, reproducible MLOps, and time-series expertise to high-impact problems in finance, climate, or research-driven product teams. I bring a blend of academic rigor, competitive programming discipline, and hands-on production deployment experience.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

Parabole.ai

Jun 2025 - Present (1 year)

Performed change point analysis, causal inference and predictions on batch and time-series data; deployed algorithms to personal GPU servers for backtesting and removed data redundancy to optimize costs.

Causal Inference Change Point Detection Time Series Analysis Python PyTorch data preprocessing

Quant Researcher

Alphatensor.ai

Jun 2025 - Aug 2025 (2 months)

Designed advanced feature-engineering pipelines to extract high-value predictive signals for financial time series and developed noise-removal and filtering methods to improve predictability.

Signal Processing Time Series Python Pandas NumPy Statistical Modeling

Algorithmic Trading Strategist

ZfenseLabs

Jun 2024 - Jun 2025 (1 year)

Developed backend systems for simulating and backtesting trading strategies, implemented classical and ML algorithms for HFT, and integrated MLOps tooling; achieved ~34% annual return with -11.20% max drawdown and 5.24 Sharpe.

Algorithmic Trading Machine Learning MLOps MLFlow Python CI CD

Local Copilot Intern

Coriolis Technologies

May 2024 - Jun 2024 (1 month)

Developed a local copilot using open-source LLMs to analyze private codebases and provide code autocompletions with on-device inference.

Large Language Models Autocompletion Python Model Fine Tuning Privacy Preserving Inference Git

Research Intern

Parabole.ai

Jun 2023 - Feb 2024 (8 months)

Generated synthetic datasets for evaluating causal inference models, designed changepoint detection techniques to identify regime shifts, and constructed causal models from observational data.

Synthetic Data Generation Causal Inference Structural Learning Python DoWhy Time Series Analysis Data Simulation

Education

Degrees, certifications, and relevant coursework

Chennai Mathematical Institute

Master of Science, Computer Science

2023 - 2025

Master of Science in Computer Science with a minor in Mathematics; completed in June 2025 with a thesis titled "Exploring Causality and Explainability in Time Series Models".