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1–2 jobs· newest first

Lead Computational Finance Scientist
The Mitre Corporation · McLean, US
$157K–$235KOn-site · Full-time
Data Scientist – Product Builder
Ferrovial · Madrid, Spain

+10K new in the last hour

Lead Computational Finance Scientist

The Mitre Corporation · Posted Aug 28, 2026

McLean, Virginia, United States
On-site
Full-time
$157K–$235K per year

8+ years

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Lead Computational Finance Scientist

Compensation

Salary compensation range and midpoint: $156,800 - $196,000 - $235,200 Annual

Responsibilities

Develop innovative, multidisciplinary approaches for analyzing financial data and trends that may impact the US financial system and markets
Provide expert analysis and/or develop research proposals on issues related to improving financial regulation and banking supervision, adopting new technologies to support distributed ledger or faster payments, or implementing advanced financial analytics
Understand US, mission partner, and adversary capabilities and assess potential threats to U.S. financial stability and security
Conduct analytic and simulation-based analyses using financial data to provide new insights which support policy-level decision making
Provide US Treasury and related sponsors with commercial and market analysis of national interest areas, and methodologies to identify mitigation alternatives

Requirements

Bachelor’s degree
Master’s degree
PhD
Nice to have: PhD in a quantitative discipline
Nice to have: Experience with U.S. Treasury

Skills

Python R Tableau Plotly ggplot2 matplotlib seaborn D3.js scikit-learn pandas dask caret dplyr data.table PostgreSQL Oracle MySQL MongoDB Neo4J Git Mercurial SVN Jupyter R Markdown Zeppelin Angular Vue React Shiny

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Data Scientist – Product Builder

Ferrovial · Posted Nov 3, 2026

Madrid, Madrid, Spain
3+ years

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Build end‑to‑end data products using agentic coding and AI tools within Ferrovial’s Digital Hub.

Responsibilities

Work closely with business stakeholders to frame problems and define objectives
Own projects from start to finish including data exploration, modelling, product build, deployment and continuous improvement
Carry out exploratory and statistical analysis on large heterogeneous datasets
Apply statistical methods such as hypothesis testing, regression, time‑series analysis and causal inference
Develop predictive and prescriptive models and manage their lifecycle with MLflow

Requirements

Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Physics, Economics or a related quantitative field

Skills

Python R SQL Git MLflow Docker Kubernetes

agentic coding tools

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