quantitative analyst developer

Qube Research & Technologies

Your future role within QRT: 
As a Quantitative Developer, you'll work in a close-knit global team of Multi-Asset Quant Developers and Researchers. Working directly with Researchers and Portfolio Managers, you'll enhance our research platform to meet the needs of a constantly evolving environment. You will have a large impact on the success of the team by recommending innovative software solutions - solving problems by building new tools and systems.
 Responsibilities 
<ul>
<li>Automate and streamline data preparation and cleaning</li>
<li>Build and support new quantitative trading framework</li>
<li>Industrialize trading strategies developed by quant researchers</li>
<li>Drive "best practice" amongst the researchers and portfolio managers</li>
<li>Continually expand and upgrade the team s software platform to accommodate the changing business needs</li>
</ul>
 Your present skillset: 
<ul>
<li>3-8 years of experience as a software engineer</li>
<li>Python language experience is a must</li>
<li>Ability to multitask, set project priorities and work in a team</li>
<li>Strong communication skills is a must</li>
<li>Ability to work in a fast-paced environment</li>
<li>Very high standards in code quality and good development practices</li>
<li>Experience in finance and/or machine learning would be beneficial</li>
</ul>

Quantitative Developer - Python

BtcDana Global

<div>
 
 
 Company Description
 
 
 
 BTC Dana is a leading next-generation financial brokerage firm based in Dubai, dedicated to revolutionizing the investment landscape. We offer a diverse range of over 500 CFD trading instruments, including FX, Cryptocurrencies, Commodities, and Stocks. Our user-friendly FinTech-designed platform and dedicated customer support make trading easy and enjoyable for everyone, ensuring transparency and fund safety.
 
 
 
 
 
 Role Description
 
 
 This is a full-time on-site role for a Quantitative Analyst (Risk), located in Dubai. The Quantitative Analyst will be responsible for developing and implementing quantitative models to analyze market risks, conducting statistical analysis, and supporting the trading platform's risk management strategies. Daily tasks will include data analysis, designing risk metrics, collaborating with various teams to optimize trading strategies.
 
 
 
 
 
 Key Responsibilities:
 
 <ul>
 <li>
 Factor &amp; Indicator Mining: Build risk/behavioural factors from historical data (e.g., markout, VPIN), integrated with risk management.
 </li>
 <li>
 User Segmentation &amp; Profiling: Classification models for retail/professional/arbitrage/HFT clients, with risk grading to drive strategy and routing optimization.
 </li>
 <li>
 PnL Attribution: Daily profit and return attribution (fees, spread, funding, basis, slippage) pipelines and anomaly notifications.
 </li>
 <li>
 Data Pipelines (Historical/Real-time): ETL of orders, trades, positions, and funds; unified definitions of metrics and dimensions.
 </li>
 <li>
 Real-time Risk Control &amp; Alerts: Dashboards (by platform/product/account), risk order detection, anomaly detection, automated risk parameter adjustment, and circuit-breaker recommendations.
 </li>
 </ul>
 
 
 
 
 
 Core Skills:
 
 
 <ul>
 <li>
 Risk Metrics: Exposure, leverage, Greeks, hedge deviation, latency/failure rate, VaR/ES, TCA, risk factor backtesting metrics (IR, Sharpe, Max Drawdown).
 </li>
 <li>
 Machine Learning: Scikit-learn; classification/regression, anomaly &amp; change-point detection, feature engineering, model drift/calibration &amp; monitoring; familiarity with PyTorch/TF.
 </li>
 <li>
 Databases &amp; Tools: SQL/Spark/Hive/ClickHouse, data modeling/partitioning/materialized views, BI tools (FineBI/PowerBI/Tableau).
 </li>
 <li>
 Data Stream Processing: Spark/Flink, Kafka/Redpanda, Airflow/Dagster; data quality frameworks (Great Expectations).
 </li>
 <li>
 Programming: Python/Java, engineering practices (testing, logging, version control).
 </li>
 <li>
 Cloud platform: Google Cloud Platform is preferred
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree or above in Computer Science, Financial Engineering, Data Science, or related fields.
 </li>
 <li>
 Familiarity with common risk control and anomaly detection algorithms (supervised/unsupervised learning, clustering, time series analysis).
 </li>
 <li>
 Prior experience in financial derivatives, leveraged trading, or FX/CFD risk management preferred.
 </li>
 <li>
 Strong risk awareness, with ability to connect models to business use cases.
 </li>
 <li>
 Strong cross-functional communication skills (collaborating with risk, trading, and development teams).
 </li>
 </ul>
</div>

Quantitative Analyst

Assam Agro Tech Ltd

Quant Trainee (Data Analyst/Developer) - RemoteRole Summary: Develop, test, and optimize data-driven trading tools. Focus on high-performance data handling, backtesting, and algorithmic execution support.Requirements:<ul><li>Strong coding skills in Python</li><li>Solid foundation in Mathematics, Statistics, or Computer Science.</li><li>Good understanding of trading will be helpful</li><li>Proactive, self-motivated, and eager to master financial/trading systems.</li></ul>Benefits:<ul><li>Monthly Stipend: &#8377;5,000 &ndash; &#8377;10,000 (Based on experience).</li><li>Key Benefit: Receive intensive, proprietary training in algorithmic trading strategies and market microstructure.</li></ul>Job Type: Full-timePay: &#8377;5,000.00 - &#8377;10,000.00 per monthWork Location: Remote

Quant Developer & Data Analyst (Algo Trading)

Trade W

<div>
 
 
 Company Description
 
 
 
 Trade W is a leading multi-asset trading platform with over seven years of industry experience, providing global users with secure, convenient, and efficient access to the financial markets.
 
 
 
 
 
 Role Description
 
 
 This is a full-time on-site role for a Quantitative
 
 Developer
 
 , located in Dubai.
 
 
 
 
 
 Responsibilities
 
 
 Market-Making Optimization &amp; Execution
 
 <ul>
 <li>
 Implement quoting logic, inventory targets, dynamic spreads, passive/active switching, and hedge intensity.
 </li>
 <li>
 Link toxicity/mark-out (e.g., VPIN/Kyle &lambda;) to spreads and hedging.
 </li>
 <li>
 Build multi-LP / cross-exchange routing and cost-aware execution
 </li>
 </ul>
 
 Strategy Research &amp; Signal Development
 
 <ul>
 <li>
 Formulate testable hypotheses for MM/stat-arb/funding-basis/order-book/flow-toxicity signals.
 </li>
 <li>
 Engineer features (L1/L2, imbalance, mark-out, volatility, liquidity/impact) and produce evidence-based research notes.
 </li>
 <li>
 Translate findings into parameterized rules and production-ready configs.
 </li>
 </ul>
 
 Backtesting &amp; Performance Evaluation
 
 <ul>
 <li>
 Build trustworthy back tests with cost/slippage/latency/partial-fill modeling and venue-specific constraints.
 </li>
 <li>
 Run walk-forward/rolling validation, capacity &amp; turnover analysis, and P&amp;L attribution (spread, fees, carry/basis, slippage).
 </li>
 <li>
 Perform stress/scenario tests; track Sharpe/IR, max DD, VaR/ES; run ablations to verify signal credibility.
 </li>
 </ul>
 
 Trading Data Analysis &amp; Live Iteration
 
 <ul>
 <li>
 Analyze orders/trades/positions for mark-out, adverse selection, TCA, and market-quality KPIs.
 </li>
 <li>
 Segment users (retail/pro/arb/HFT) to inform MM parameters and routing.
 </li>
 <li>
 Maintain daily dashboards &amp; alerts; monitor backtest&harr;live drift and close gaps quickly.
 </li>
 <li>
 Run parameter/signal A/B experiments; publish concise weekly updates and quarterly roadmaps.
 </li>
 <li>
 Keep runbooks for events/new listings (risk bands, spreads, leverage) and coordinate rollouts with Dev/Risk.
 </li>
 </ul>
 
 Framework &amp; Systems
 
 <ul>
 <li>
 Design an end-to-end framework where research = backtest = simulation = production (unified data, cost/latency models, parameterized configs, experiment tracking, auto-reports).
 </li>
 <li>
 Real-time risk monitoring: inventory/exposure/leverage/hedge deviation/latency/failure-rate with anomaly detection, circuit-breakers, grade-down, and auto-recovery.
 </li>
 </ul>
 
 
 
 
 Must-have
 
 <ul>
 <li>
 Languages:
 
 C++
 
 </li>
 <li>
 Financial modeling &amp; statistics (probability/time-series, microstructure awareness); comfort with perps/futures, funding &amp; basis.
 </li>
 <li>
 Data analysis: Python (pandas/numpy/numba/asyncio/statsmodels/scikit-learn) and strong SQL; careful EDA and reproducible notebooks.
 </li>
 <li>
 Backtesting discipline: cost/impact modeling, leakage controls, validation hygiene.
 </li>
 <li>
 Engineering mindset: clean code, testing, ability to convert research into robust production rules/services.
 </li>
 <li>
 Clear communication: crisp writing, explicit assumptions, defensible conclusions for business/risk stakeholders.
 </li>
 <li>
 2-8 years of experience
 </li>
 </ul>
 
 
 
 
 Tech Stack (reference)
 
 <ul>
 <li>
 Languages: C++, Java, Python, SQL
 </li>
 <li>
 Data: PostgreSQL, ClickHouse, kdb+
 </li>
 <li>
 Analysis/Modeling: NumPy, pandas, statsmodels, scikit-learn, PyTorch/TensorFlow, cvxpy, QuantLib, arch
 </li>
 <li>
 Backtesting: vectorbt, backtrader, zipline
 </li>
 <li>
 Visualization: Matplotlib, Seaborn, Plotly, Tableau/PowerBI
 </li>
 <li>
 Workflow: Jupyter, Airflow/Dagste, Git
 </li>
 <li>
 Crypto(Optional): web3.py/ethers/solana-py, Dune/Flipside, Safe/Fireblocks
 </li>
 </ul>
 
 
 
 
 Nice-to-have
 
 <ul>
 <li>
 Order-book microstructure, MM/inventory control; toxicity metrics (mark-out/VPIN/Kyle &lambda;).
 </li>
 <li>
 ClickHouse/PostgreSQL, materialized views, high-throughput writes/queries; dashboards (Metabase/Superset/Plotly); experiment/version tracking.
 </li>
 <li>
 Streaming &amp; orchestration: Kafka/Redpanda, Flink or Spark Streaming, Airflow/Dagster; data quality (e.g., Great Expectations).
 </li>
 <li>
 Systems &amp; deployment: Linux, Docker/K8s, Prometheus/Grafana, GitHub Actions, observability/traceability.
 </li>
 <li>
 Production MM or cross-exchange arb track record; FIX/REST/WebSocket integrations (Binance/OKX/Bybit, etc.).
 </li>
 <li>
 Low-latency optimization (zero-copy, lock-free queues, batch I/O, kernel/network tuning).
 </li>
 <li>
 DEX/on-chain analytics (Dune/The Graph; web3.py/ethers/solana-py)
 </li>
 </ul>
</div>

Quantitative Developer (C++)

Universis Capital Partner

C++ Quant Developer Engineer technology - trading developer / hybrid / full time 
Who are we looking for: C++ Quant Developer Engineer We are looking for a talented quant developer engineer to create secure and functional code. You will provide quality coding solutions for both simple applications and complex information or systems. The candidate must have a passion for technology and code creation. Attention to detail and an analytical mind are essential qualities for a successful application. Design and build superior and innovative software by writing clean and flawless code. The objective is to work directly with our team of traders, engineers, analysts and data scientists to develop our trading algorithmic infrastructure, including; development and creation of trading algorithms, bringing new functionality, integration of third party APIs, integration of new liquidity sources, enhancements to current infrastructure, structuring of financial systems, with a special focus on developing low latency trading systems. The ideal candidate would be passionate about algorithmic and crypto trading, specialized in building low level systems. With knowledge in algorithmic trading based on Data Mining, Big data, Quants, Machine Learning, with predictive and risk management capabilities to implement high frequency and low latency systems, HFT, Market Making, arbitrage systems.
 Responsibilities: <ul> <li>Programming and implementation of commercial algorithms.</li> <li>Collaborate with business analysts and quants to produce algorithm designs and improve agility and execution of strategies.</li> <li>Develop advanced tick-by-tick backtesting simulation systems to enable rapid strategy prototyping and improved research accuracy.</li> <li>Increase performance management by improving risk, quantification.</li> <li>Interact directly with the business or provide support to the commercial, development and operational teams, supervising to implement changes, technological improvements and solve incidents or problems.</li> <li>Transform designs and specifications into high performance code in the appropriate language, creating high quality code with technical documentation.</li> <li>Integrate individual code solutions into higher-level systems. Work to ensure high performance, security and scalability of business applications.</li> <li>Monitor periodically to ensure that it produces the desired results and perform debugging when necessary.</li> <li>Performing upgrades to make code and systems more secure and efficient. Participating in product quality control.</li> <li>Collaborate in the development of our ultra-low latency commercial platform.</li> <li>Integraci n de las API con terceros; intercambios, bancos y corredores entre otros.</li> <li>Design, development and improvement of main libraries.</li> <li>Collaborate with other teams, including; strategy reviews, code and common programming advice.</li> </ul>
 Requirements: <ul> <li>Bachelor's degree in Computer Science, Computer Science or similar.</li> <li>Strong programming skills in C++, Java, XML, Python.</li> <li>Excellent knowledge with relational databases, MySQL, Mongo, Influx technologies.</li> <li>An analytical and problem-solving mindset.</li> <li>Demonstrable ability to discover and correct bugs in code.</li> <li>Ability to work independently, but in a collaborative team environment.</li> <li>Deep curiosity about financial trading and the digital blockchain ecosystem.</li> <li>Entrepreneurial mindset, persistent and disciplined with a high degree of motivation and involvement.</li> <li>High level of English, fluent oral and written communication.</li> </ul>
 Experience: <ul> <li>More than 2 years of proven experience as a C++ programmer.</li> <li>Experience in developing financial algorithms, with predictive analytics and risk control.</li> <li>Experience with AWS, Google Cloud, Linux.</li> <li>Experience in the financial sector: algorithmic developer, High Frequency Trading, Derivatives Trading, Options trading.</li> </ul>
 Other required skills: <ul> <li>Data Mining, Big data, Quants, Machine Learning, HFT, Market Making, Pure and cross, Arbitrage of different modalities.</li></ul>

C++ Quant Developer Engineer

Morningstar

<div>Position: Senior Principal Quantitative Analyst
Department: Managed Investment Data (MID) &ndash; Quality &amp; Transformation
No of Positions: 1
Shift: General Shift<h3 class="jobSectionHeader">
Job Description</h3>
The Senior Principal Quantitative Analyst plays a critical role in ensuring the accuracy, integrity, and reliability of quantitative data that powers Morningstar&rsquo;s financial models, analytics, and decision-making processes.
This role is a cornerstone of the Managed Investment Data (MID) program, which collects, standardizes, and enriches global fund data&mdash;supporting investors, advisors, and institutions through trusted data and insight.
The analyst will lead quantitative data quality design and implementation, develop AI/ML-based validation frameworks, and collaborate with cross-functional teams to strengthen data governance and model readiness.
This role reports to the Director, Quality &amp; Transformation within the Managed Investment Data team based in Mumbai.<h3 class="jobSectionHeader">
Job Responsibilities</h3><ul><li>
Lead the design, implementation, and enhancement of quantitative data quality frameworks, encompassing statistical validation and anomaly detection.</li><li>
Develop AI/ML-driven predictive quality checks, enabling proactive data error prevention and model trustworthiness.</li><li>
Apply advanced statistical methodologies &mdash; linear/non-linear modeling, time series analysis, and Bayesian inference &mdash; to detect quality drifts and signal inconsistencies.</li><li>
Collaborate with quantitative researchers, data scientists, and engineers to ensure data readiness for quantitative models and investment algorithms.</li><li>
Create automated, scalable, and auditable data validation pipelines, supporting real-time data monitoring and exception reporting.</li><li>
Partner with stakeholders to uphold data governance, privacy, and regulatory compliance standards (MiFID, ESMA, SEC).</li><li>
Mentor and guide junior analysts, fostering a culture of excellence, continuous learning, and innovation in quantitative analysis.</li><li>
Communicate complex data quality insights and statistical findings in simple terms to senior leadership and non-technical stakeholders.</li><li>
Drive innovation through automation, reproducible modeling pipelines, and deployment of ML-based data correction systems.</li><li>
Contribute to the modernization of Morningstar&rsquo;s data architecture by integrating data observability, telemetry, and metadata-driven quality measures.</li></ul><h3 class="jobSectionHeader">
Requirements</h3><ul><li>
Strong foundation in quantitative finance, econometrics, and applied statistics.</li><li>
Deep understanding of financial instruments, fund structures, and performance modeling.</li><li>
Proven ability to work with large-scale, structured and unstructured data.</li><li>
Excellent analytical, problem-solving, and statistical reasoning skills.</li><li>
Strong stakeholder management, communication, and presentation skills.</li><li>
Ability to work in a cross-functional, fast-paced environment, and lead through influence.</li></ul><h3 class="jobSectionHeader">
Desired Candidate Profile</h3><ul><li>
Master&rsquo;s degree in Statistics, Mathematics, Financial Engineering, Data Science, or Quantitative Finance.</li><li>
Professional certifications such as CFA, FRM, CQF, or Six Sigma Black Belt preferred.</li><li>
10+ years of experience in quantitative analytics, model validation, or data quality engineering within financial services, asset management, or fintech.</li><li>
Expertise in Python, R, SQL, and familiarity with tools such as MATLAB, SAS, or TensorFlow.</li><li>
Experience in AWS ecosystem (S3, RDS, Glue, Athena) and modern data quality platforms.</li><li>
Hands-on experience with AI/ML frameworks (scikit-learn, PyTorch, TensorFlow) for anomaly detection and predictive data correction.</li><li>
Familiarity with data governance and regulatory standards (GDPR, SEC, ESMA, MiFID).</li><li>
Proficiency in Lean, Agile, and automation-first approaches for process improvement.</li><li>
Entrepreneurial mindset with a passion for innovation and scalability.</li><li>
Strong leadership, mentorship, and collaboration abilities.</li><li>
Flexible to adapt to evolving data and technology landscapes.</li></ul><h3 class="jobSectionHeader">
Key Competencies</h3><ul><li>
Statistical Expertise: Deep proficiency in hypothesis testing, regression modeling, and time-series forecasting.</li><li>
AI/ML Integration: Building and deploying predictive quality and anomaly detection models.</li><li>
Automation Mindset: Experience with data pipelines, ETL automation, and observability frameworks.</li><li>
Data Governance: Comprehensive understanding of metadata management, lineage, and auditability.</li><li>
Business Acumen: Translating technical insights into actionable business intelligence.</li><li>
Leadership: Guiding teams through analytical rigor, innovation, and continuous improvement.</li></ul>
Morningstar is an equal opportunity employer.
We celebrate diversity and are committed to creating an inclusive environment for all employees.
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity</div>

Senior Principal Quantitative Analyst

Information Technology Senior Management Forum

<div><div>Posted Date
10/24/2025
</div><div>Description
<div>Principal Quantitative Analyst - CMA Predictive Analytics
At Capital One data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Quantitative Analyst at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
The Quantitative Analyst teams at Capital One offer a unique opportunity to be part of a dynamic analytics and modeling team focused on developing behavior and valuation models for balance sheet portfolios. These portfolios can range from investment securities, retail and commercial deposits, mortgage loans, derivatives, and other fixed income products. Successful candidates will partner cross-functionally with business throughout the company to deliver breakthrough analytical solutions to support a winning strategy in a continually changing business environment.
Responsibilities and Skills:<ul><li>Partner with the various lines of business to develop and enhance Capital Markets modeling and analytical framework, such as deposit predictions, derivatives models and fixed income models.</li><li>Work across Capital One entities to create novel analytical solutions to challenging business problems.</li><li>Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.</li><li>Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.</li><li>Identify opportunities to apply quantitative methods or machine learning to improve business performance.</li><li>Apply deep expertise in mathematics, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.</li><li>Providing technical guidance to business leadership.</li><li>Communicate technical subject matter clearly and concisely to individuals from various backgrounds.</li><li>Understand and navigate Risk Management Software to enable business analysis.</li></ul> 
Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation.
Successful candidates would possess:<ul><li>Deep understanding of quantitative modeling in relation to finance, deposit behaviors, capital markets and investment portfolio modeling principles.</li><li>Extensive experience in Python or other object-oriented language.</li><li>Ability to clearly communicate modeling results to a wide range of audiences.</li><li>Drive to develop and maintain high quality and transparent model documentation.</li><li>Strong written and verbal communication skills.</li><li>Strong presentation skills.</li><li>Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring.</li></ul> 
Basic Qualifications:
<ul><li>Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:</li><li>A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics</li><li>A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics</li><li>A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)</li></ul>
Preferred Qualifications:<ul><li>Master&rsquo;s Degree or PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related discipline.</li><li>1+ year of experience with Python, R or other statistical analyst software</li><li>2+ years of experience with data analysis</li><li>1+ year of experience manipulating and analyzing large data sets.
</li></ul>Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $158,600 - $181,000 for Prin Assoc, Quant Analysis 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Principal Quantitative Analyst - CMA Predictive Analytics
At Capital One data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Quantitative Analyst at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
The Quantitative Analyst teams at Capital One offer a unique opportunity to be part of a dynamic analytics and modeling team focused on developing behavior and valuation models for balance sheet portfolios. These portfolios can range from investment securities, retail and commercial deposits, mortgage loans, derivatives, and other fixed income products. Successful candidates will partner cross-functionally with business throughout the company to deliver breakthrough analytical solutions to support a winning strategy in a continually changing business environment.
Responsibilities and Skills:<ul><li>Partner with the various lines of business to develop and enhance Capital Markets modeling and analytical framework, such as deposit predictions, derivatives models and fixed income models.</li><li>Work across Capital One entities to create novel analytical solutions to challenging business problems.</li><li>Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.</li><li>Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.</li><li>Identify opportunities to apply quantitative methods or machine learning to improve business performance.</li><li>Apply deep expertise in mathematics, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.</li><li>Providing technical guidance to business leadership.</li><li>Communicate technical subject matter clearly and concisely to individuals from various backgrounds.</li><li>Understand and navigate Risk Management Software to enable business analysis.</li></ul> 
Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation.
Successful candidates would possess:<ul><li>Deep understanding of quantitative modeling in relation to finance, deposit behaviors, capital markets and investment portfolio modeling principles.</li><li>Extensive experience in Python or other object-oriented language.</li><li>Ability to clearly communicate modeling results to a wide range of audiences.</li><li>Drive to develop and maintain high quality and transparent model documentation.</li><li>Strong written and verbal communication skills.</li><li>Strong presentation skills.</li><li>Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring.</li></ul> 
Basic Qualifications:
<ul><li>Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:</li><li>A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics</li><li>A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics</li><li>A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)</li></ul>
Preferred Qualifications:<ul><li>Master&rsquo;s Degree or PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related discipline.</li><li>1+ year of experience with Python, R or other statistical analyst software</li><li>2+ years of experience with data analysis</li><li>1+ year of experience manipulating and analyzing large data sets.
</li></ul>Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $158,600 - $181,000 for Prin Assoc, Quant Analysis 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>
</div><div>Salary
158,600.00 - 181,000.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Principal Quantitative Analyst - CMA Predictive Analytics

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