Job Title: Data Scientist
Company: Quanted
Location: Remote
About Quanted
Quanted is the quantitative matching engine between quants and data.
We build secure, on-prem platform automates the tedious process of identifying which datasets improve a model’s performance. In minutes, it delivers clear, explainable recommendations helping quants uncover high-value data to enrich their models and extract more from what they already use, all without exposing IP on either side. Data vendors get high-intent referrals and real insight into quant demand, while quants get actionable insights to refine their strategies more efficiently.
Role Overview
We’re seeking a highly analytical and execution-oriented Data Scientist with a strong background in finance and machine learning. You will be responsible for designing and maintaining robust pipelines for training, validating, and deploying predictive models on time series data. Your work will directly support our efforts to generate actionable insights from financial datasets and automate model development workflows.
What You'll Do
- Develop and maintain automated machine learning pipelines for training, validation, and backtesting.
- Apply and tune traditional ML algorithms (e.g., decision trees, SVMs, ensemble models) on financial time series data.
- Design experiments for model selection and robust validation, including walk-forward, rolling windows, and nested CV.
- Engineer relevant features from complex time series and structured financial data.
- Apply linear (e.g., Ridge, Lasso, PCA) and non-linear models (e.g., kernel methods, boosting).
- Implement unsupervised learning techniques such as clustering and dimensionality reduction to discover latent structure in financial datasets.
- Collaborate with engineers to productionize models in a modular and reproducible format.
- Document processes clearly and communicate findings to both technical and non-technical stakeholders.
We're Looking For Someone With
- 3+ years of experience as a data scientist or quant in the finance or fintech industry.
- Strong knowledge of time series forecasting, signal generation, and model evaluation in dynamic environments.
- Expertise in Python and ML libraries such as scikit-learn, XGBoost, LightGBM, and statsmodels.
- Experience with automated training/validation pipelines, ML workflow orchestration (e.g., Airflow, Prefect, or custom scripting).
- Proficiency in statistical testing, feature selection, and overfitting prevention techniques.
- Solid experience with clustering methods (e.g., k-means, DBSCAN, hierarchical clustering).
- Familiarity with SQL and working with large tabular datasets.
Bonus If You Have
- Familiarity with financial modeling, including return forecasting, risk modeling, and portfolio construction.
- Experience working with multi-timeframe data or high-frequency datasets.
- Exposure to meta-labeling, model stacking, or other ensemble techniques in finance.
- Understanding of causal inference or explainable AI methods in the context of trading strategies is a plus.
- Experience with ClickHouse, ArcticDB, or other high-performance analytical data stores is a plus.
How You Work
- Strong critical thinking and hypothesis-driven development approach.
- Comfortable working in a fast-paced, high-uncertainty startup environment.
- Clear communicator with ability to justify modeling decisions and translate findings into actionable insights.
What you'll Receive
- Competitive Compensation: Attractive salary package with potential equity options.
- Professional Growth: Access to the latest tools and tech in data science and finance, with abundant learning opportunities.
- Flexible hours and remote work options in a supportive and inclusive company culture. Working alongside our CTO with direct mentorship and collaboration.
- Hands-on experience in cutting-edge AI applications for quantitative finance: Opportunity to work on high-impact projects that influence investment decision-making processes at top global quant funds.
Quanted is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.