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Backtesting Jobs in New Jersey (NOW HIRING)

Quant Developer

Jersey City, NJ · On-site

$80 - $90/hr

Build research and backtesting frameworks integrating AI models with historical data. * Translate quantitative and ML research into production-ready, resilient systems. * Integrate AI models into ...

Perform backtesting and simulation of trading strategies. * Validate financial models and ensure the accuracy of calculations. * Contribute to the ongoing improvement of analytics infrastructure and ...

Perform backtesting and simulation of trading strategies. * Validate financial models and ensure the accuracy of calculations. * Contribute to the ongoing improvement of analytics infrastructure and ...

Perform backtesting and simulation of trading strategies. * Validate financial models and ensure the accuracy of calculations. * Contribute to the ongoing improvement of analytics infrastructure and ...

... backtesting. • Experience working with NoSQL and vector databases to store, index, and query large-scale semi-structured and unstructured datasets. • Experience designing and operating large ...

... backtesting. • Experience working with NoSQL and vector databases to store, index, and query large-scale semi-structured and unstructured datasets. • Experience designing and operating large ...

... backtesting. • Experience working with NoSQL and vector databases to store, index, and query large-scale semi-structured and unstructured datasets. • Experience designing and operating large ...

... backtesting. * Experience working with NoSQL and vector databases to store, index, and query large-scale semi-structured and unstructured datasets. * Experience designing and operating large-scale ...

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Backtesting information

What are the key skills and qualifications needed to thrive as a Backtesting Analyst, and why are they important?

To thrive as a Backtesting Analyst, you need a strong background in quantitative analysis, statistics, programming (typically in Python or R), and familiarity with financial markets, usually supported by a degree in mathematics, finance, or a related field. Proficiency with backtesting platforms (such as QuantConnect or Zipline), data analysis tools, and version control systems like Git is often required. Attention to detail, critical thinking, and strong problem-solving abilities are key soft skills that help ensure robust model evaluation and development. These skills are vital for accurately assessing trading strategies and minimizing risk in real-world financial applications.

What is backtesting?

Backtesting is the process of evaluating a trading strategy or investment model by applying it to historical market data. This helps traders and analysts see how the strategy would have performed in the past, which can provide insights into its potential effectiveness and risks. While backtesting can help identify strengths and weaknesses, it's important to remember that past performance is not always indicative of future results. The reliability of backtesting depends on data quality, strategy design, and how well it simulates real trading conditions.

What are some common challenges faced when backtesting trading strategies, and how can they be managed?

One common challenge in backtesting trading strategies is the risk of overfitting, where a model performs exceptionally well on historical data but fails in live markets. Data quality and availability can also pose issues, as incomplete or inaccurate data may skew results. To manage these challenges, it's important to use out-of-sample testing, robust data cleaning processes, and to validate strategies on multiple datasets. Collaborating with quantitative analysts and developers can also help ensure the backtesting process is thorough and reliable.

What is the difference between Backtesting vs Quantitative Analyst?

AspectBacktestingQuantitative Analyst
Primary RoleTesting trading strategies using historical dataDeveloping and implementing quantitative models for investment decisions
Required SkillsData analysis, programming, finance knowledgeMathematics, programming, financial theory
Work EnvironmentTrading firms, hedge funds, financial institutionsAsset management firms, hedge funds, banks
CertificationsOften none required, but CFA or CQF helpfulCFA, CQF, or advanced degrees common

Backtesting focuses on evaluating trading strategies with historical data, while a Quantitative Analyst develops models to inform investment decisions. Both roles require strong analytical skills and finance knowledge but differ in scope and responsibilities.

What cities in New Jersey are hiring for Backtesting jobs? Cities in New Jersey with the most Backtesting job openings:
Infographic showing various Backtesting job openings in New Jersey as of July 2026, with employment types broken down into 1% Internship, 97% Full Time, 1% Part Time, and 1% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Software Engineering Technical Team Lead

Spgi

Princeton, NJ

Full-time

Medical, Retirement

Posted 18 days ago


Job description

About the Role:

Grade Level (for internal use):

13

Role Summary

We are seeking a Technical Team Lead - AI, AWS, Java Full-Stack, Financial Platforms to lead the design, development, and delivery of index calculation and back testing platform. This role combines hands-on Java full-stack engineering, AWS cloud development, AI-assisted software delivery, and technical leadership across a financial technology platform.

The Technical Team Lead will guide a team of engineers in building scalable backend services, modern user interfaces, financial calculation workflows, back testing capabilities, data integrations, automated testing frameworks, and AI-assisted QA/evaluation routines. The role requires strong technical judgment, practical leadership, and the ability to translate financial methodology requirements into reliable, auditable, and production-ready software.

This is a hands-on leadership role. The successful candidate will be expected to define technical direction, mentor developers, review architecture and code, collaborate with business and quantitative stakeholders, and contribute directly to critical platform components.

Key Responsibilities

Technical Leadership

  • Lead the engineering delivery of an AI-enabled financial platform for index calculation, options analytics, back testing, and workflow execution.

  • Define technical architecture, implementation standards, coding practices, testing expectations, and delivery patterns for the engineering team.

  • Guide developers through complex design decisions involving Java services, frontend architecture, AWS workflows, data integration, AI-assisted development, and calculation accuracy.

  • Partner with product owners, quantitative analysts, QA teams, infrastructure teams, data teams, and business stakeholders to convert requirements into clear technical plans.

  • Lead design reviews, code reviews, sprint technical planning, production readiness reviews, and technical risk assessments.

  • Mentor engineers in Java full-stack development, cloud-native design, financial calculation systems, automated testing, and responsible use of AI-assisted engineering tools.

  • Ensure the platform is scalable, secure, maintainable, observable, auditable, and aligned with financial methodology and operational requirements.

Hands-On Java Full-Stack Development

  • Design and develop backend services using Java, Spring Boot, REST APIs, and enterprise application patterns.

  • Build platform components for index calculation, backtesting, data processing, workflow orchestration, exception handling, validation, and reporting.

  • Implement financial calculation logic based on methodology specifications, including options-based strategies, rebalancing rules, pricing inputs, market calendars, and historical backtesting assumptions.

  • Develop modern frontend applications using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS.

  • Build user interfaces for index setup, backtest configuration, workflow monitoring, calculation review, validation results, exception management, dashboards, and reporting.

  • Ensure strong integration between frontend applications, backend APIs, authentication flows, data services, and cloud workflows.

AI-Assisted Engineering and Spec-Driven Development

  • Apply Spec-Driven Development practices to convert financial methodology documents, business requirements, and technical specifications into testable software components.

  • Use AI-assisted engineering workflows to support planning, code generation, refactoring, test creation, documentation, and quality review.

  • Review AI-generated or AI-assisted code for correctness, maintainability, security, performance, test coverage, and alignment with platform standards.

  • Help establish team practices for responsible AI-assisted development, including review checklists, validation gates, test coverage expectations, and documentation standards.

  • Support AI-assisted QA and evaluation routines for generated code, calculation outputs, regression testing, and backtest validation.

AWS, Data, and Platform Engineering

  • Design and implement AWS-based platform components using services such as AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, and AWS RDS.

  • Build workflow orchestration for index calculations, backtest execution, data validation, exception handling, approvals, and operational monitoring.

  • Integrate with data platforms including AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), data lakes, market data sources, reference data platforms, and analytical data pipelines.

  • Ensure data lineage, audit trails, input/output traceability, logging, alerting, and operational controls are built into the platform.

  • Support CI/CD, infrastructure automation, deployment validation, monitoring, and production support practices.

Required Experience

  • 12+ years of software engineering experience, with significant experience in Java full-stack development and enterprise platform delivery.

  • 5+ years of technical leadership experience, including mentoring engineers, leading design discussions, reviewing code, and guiding delivery teams.

  • Strong hands-on experience with Java, Spring Boot, REST APIs, microservices, relational databases, and backend service design.

  • Hands-on frontend development experience using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS.

  • Experience designing and delivering large-scale systems involving distributed services, workflow orchestration, data processing, APIs, and production operations.

  • Experience with AWS cloud-native development, including compute, storage, orchestration, security, monitoring, logging, and managed databases.

  • Strong understanding of automated testing, CI/CD, code quality, observability, secure development, and production readiness.

  • Experience or strong interest in financial platforms, especially index calculation, options analytics, derivatives, equities, portfolio analytics, backtesting, risk systems, or capital markets technology.

  • Ability to interpret detailed financial methodology specifications and translate them into reliable, testable, and auditable software designs.

  • Exposure to GenAI engineering, AI-assisted coding, agentic development workflows, Claude Code, Claude Code CLI, Spec Kit, or Spec-Driven Development is highly desirable.

Preferred Technical Stack

  • Backend:Java, Spring Boot, REST APIs, microservices, JPA/Hibernate, Maven/Gradle, concurrency, batch processing, and enterprise integration patterns.

  • Frontend:React, Angular, or Vue; TypeScript; JavaScript; HTML; CSS; reusable components; dashboards; forms; data grids; charts; and responsive UI design.

  • Cloud:AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, RDS, and cloud-native security patterns.

  • Data Platforms:AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), relational databases, data pipelines, market data integration, reference data, and analytical data processing.

  • AI Engineering:AI-assisted development, Spec-Driven Development, Claude Code, Claude Code CLI, Spec Kit, automated QA/evaluation routines, and human-reviewed generated code.

  • DevOps and Quality:CI/CD, automated testing, integration testing, regression testing, performance testing, logging, monitoring, alerting, and production support.

Financial Domain Knowledge

The ideal candidate should have experience or strong working interest in financial systems involving calculation-heavy workflows. Relevant areas include:

  • Index calculation methodologies, index levels, divisor logic, rebalancing, weighting, corporate actions, calendars, and daily calculation cycles.

  • Options-based strategies such as covered call, put write, collar, volatility-based, delta-based, or rules-based options strategies.

  • Backtesting concepts such as historical simulation, look-ahead bias prevention, survivorship bias, transaction assumptions, rebalance simulation, and reproducibility.

  • Market data concepts including prices, option chains, strikes, expiries, implied volatility, rates, dividends, corporate actions, and reference data.

  • Validation practices including golden datasets, tolerance checks, independent calculation verification, reconciliation, audit trails, and exception handling.

Success Measures

  • Leads the team in delivering a scalable, secure, and reliable index calculation and backtesting platform.

  • Produces and guides high-quality Java full-stack implementation across backend services, frontend applications, APIs, workflows, and data integrations.

  • Converts financial methodology specifications into tested, reproducible, and auditable platform logic.

  • Establishes strong engineering practices for code quality, automated testing, observability, documentation, and production readiness.

  • Uses AI-assisted development responsibly to improve delivery speed while maintaining human review, financial accuracy, and software quality.

  • Builds strong collaboration across engineering, quantitative analysis, QA, infrastructure, product, and business stakeholders.

  • Mentors developers and raises the overall technical capability of the team.

Compensation/Benefits Information:

(This section is only applicable to US candidates)

S&P Global states that the anticipated base salary range for this position is $142,000 to $215,000. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses and certifications.

In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.

This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.

About S&P Global Dow Jones Indices

At S&P Dow Jones Indices, we provide iconic and innovative index solutions backed by unparalleled expertise across the asset-class spectrum. By bringing transparency to the global capital markets, we empower investors everywhere to make decisions with conviction. We're the largest global resource for index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500 and the Dow Jones Industrial Average. More assets are invested in products based upon our indices than any other index provider in the world. With over USD 7.4 trillion in passively managed assets linked to our indices and over USD 11.3 trillion benchmarked to our indices, our solutions are widely considered indispensable in tracking market performance, evaluating portfolios and developing investment strategies.

S&P Dow Jones Indices is a division of S&P Global (NYSE: SPGI). S&P Global is the world's foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world's leading organizations navigate the economic landscape so they can plan for tomorrow, today. For more information, visit www.spglobal.com/spdji.

What's In It For You?

Our Mission:

Advancing Essential Intelligence.

Our People:

We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values:

Integrity, Discovery, Partnership


Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
Benefits:

We take care of you, so you cantake care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global.
Our benefits include:

  • Health & Wellness: Health care coverage designed for the mind and body.

  • Flexible Downtime: Generous time off helps keep you energized for your time on.

  • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.

  • Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.

  • Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.

  • Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference.

For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries

Global Hiring and Opportunity at S&P Global:

At S&P Global, we are committed to fostering a connected...