1

Algorithmic Trading Jobs in Columbus, OH (NOW HIRING)

... advanced algorithms. * Shift to Predictive Operations: Equip the organization with modeling ... Global Procurement, Trade, and Ecosystem Strategy * Simplify and Strengthen the Partner Landscape:

Senior Specialty Protocol Engineer

Columbus, OH

$100.90K - $138.60K/yr

Distributed Systems: 1+ year of experience with BFT consensus algorithms, P2P networking, and state ... UTXO Model trade-offs in privacy-preserving ledgers Job Expectations: * This position offers a ...

New

Underpinned by a unique biometric algorithm, Biosite provides market-leading software solutions for ... Working closely with new customers to build successful trading relationships. * Developing your own ...

Algorithmic Trading information

See Columbus, OH salary details

$69.6K

$80.1K

$87.8K

How much do algorithmic trading jobs pay per year?

As of May 29, 2026, the average yearly pay for algorithmic trading in Columbus, OH is $80,120.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,700.00 and $85,000.00 per year, depending on experience, location, and employer.

What Is Algorithmic Trading?

Algorithmic trading involves trading in equities, currencies, or other financial instruments using computer programs. A trading program uses an algorithm to calculate current market conditions. This trading method is automated, so the program buys or sells the financial instrument when the algorithm says that the market meets all the requirements for a profitable trade. To create an algorithm, you perform mathematical and statistical analysis, also known as quantitative analysis, on an exchange or equity. After creating an algorithm with defined trading rules, you test it using historical market data. While this is primarily a technical field, you also need an understanding of the market.

What are the key skills and qualifications needed to thrive as an Algorithmic Trader, and why are they important?

To thrive as an Algorithmic Trader, you need a strong background in quantitative analysis, programming (often Python, C++, or Java), and a solid understanding of financial markets, typically supported by a degree in mathematics, engineering, finance, or computer science. Familiarity with statistical modeling tools, trading platforms, and backtesting systems is essential, and certifications such as CFA or FRM can be advantageous. Superior problem-solving skills, attention to detail, and the ability to work under pressure set standout professionals apart in this field. These skills are crucial to developing, implementing, and refining trading strategies that can operate profitably and reliably in fast-moving financial environments.

What are the main challenges faced by professionals in algorithmic trading, and how can they be addressed?

Professionals in algorithmic trading often encounter challenges such as developing strategies that remain effective in rapidly changing markets, minimizing latency for faster execution, and managing the risks associated with automated trading systems. To address these challenges, it's essential to stay updated with the latest market trends and technological advancements, conduct rigorous backtesting of algorithms, and implement robust risk management protocols. Collaboration with quantitative analysts, software engineers, and risk managers is also key to ensuring strategies are both innovative and resilient.

What is the difference between Algorithmic Trading vs Quantitative Analyst?

AspectAlgorithmic TradingQuantitative Analyst
Required CredentialsDegree in finance, computer science, or related field; programming skillsDegree in mathematics, statistics, or finance; strong analytical skills
Work EnvironmentTrading firms, hedge funds, financial institutions; fast-pacedInvestment banks, asset management firms; research-focused
Employer & Industry UsageUsed to automate trading strategiesDevelops models to inform trading decisions

While both roles involve quantitative skills and finance knowledge, Algorithmic Traders focus on implementing automated trading systems, whereas Quantitative Analysts develop models and strategies that may be used by traders or firms. The roles often overlap but differ mainly in their primary focus: execution versus modeling.

What are popular job titles related to Algorithmic Trading jobs in Columbus, OH? For Algorithmic Trading jobs in Columbus, OH, the most frequently searched job titles are:
What job categories do people searching Algorithmic Trading jobs in Columbus, OH look for? The top searched job categories for Algorithmic Trading jobs in Columbus, OH are:
Infographic showing various Algorithmic Trading job openings in Columbus, OH as of May 2026, with employment types broken down into 72% Full Time, 18% Part Time, and 10% Contract. Highlights an 57% Physical, 15% Hybrid, and 28% Remote job distribution, with an average salary of $80,120 per year, or $38.5 per hour.
Product Manager, AI Platform

Product Manager, AI Platform

JPMorgan Chase & Co.

Columbus, OH • On-site

Full-time

Medical, Retirement

Posted 20 hours ago


JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 466 frontline employees who took The Breakroom Quiz

45th of 141 rated banks


Job description

Job Description
You enjoy shaping the future of product innovation as a hands-on leader, driving measurable value for customers, guiding successful launches, and exceeding expectations. Join a dynamic Corporate & Investment Banking team to build and scale a production entity data platform that enables trusted decisions across front-office workflows, risk and controls, and AI-driven applications.
As a Product Manager in the C360 team, you are an integral part of the organization that delivers core data products used every day across the firm. You will own the end-to-end product life cycle for resolving millions of organizational records from internal systems and third-party providers into a single, trusted global universe of entities, and producing an arbitrated "golden profile" that downstream platforms rely on. This is a product ownership role focused on shipping capabilities into production at scale, not an advisory or analytics-only role and requires strong operating discipline, technical fluency, and cross-functional leadership.
Job responsibilities
  • Develops a product strategy and product vision that delivers customer value by establishing a single, trusted, global universe of organizations and an arbitrated "golden profile" that downstream teams and platforms can rely on in production.
  • Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap, including partnering with front-office, operations, and control stakeholders to define measurable outcomes for match quality, duplicate reduction, profile completeness, and adoption.
  • Owns, maintains, and develops a product backlog that enables development to support the overall strategic roadmap and value proposition, translating business needs into clear, testable requirements for entity resolution, attribute arbitration, challenge-and-override workflows, and data onboarding patterns.
  • Builds the framework and tracks the product's key success metrics such as cost, feature and functionality, risk posture, and reliability, including precision/recall and false positive/negative rates, resolution throughput and cycle time, duplicate creation rates, golden profile correctness and completeness, and service-level targets for adjudication workflows.
  • Leads delivery of entity resolution at scale across internal systems and third-party sources by balancing deterministic rules with machine learning-assisted matching, ensuring resolution decisions are explainable, traceable, and auditable for downstream reliance.
  • Owns the arbitration and "golden record" capabilities that select best attribute values using configurable logic (for example, consensus and recency), including workflows that allow expert challenge, override, and safe propagation of corrections with full provenance.
  • Defines a third-party data onboarding strategy and operating model, prioritizing integrations based on business value and readiness, setting quality and documentation standards, and establishing scalable onboarding patterns that prevent uncontrolled schema sprawl.
  • Delivers diagnostic and operational tooling that enables users and operators to understand why entities matched or did not match, how attribute selections were made, and where data quality issues are creating adverse outcomes.
  • Introduces AI- and agent-assisted processing patterns to improve throughput and reduce manual intervention, while maintaining appropriate governance, human-in-the-loop controls, and objective evaluation of model performance over time.
  • Partners closely with engineering, applied machine learning, architecture, data governance, and business stakeholders to manage dependencies, ensure resiliency and stability, and drive executive-ready communication on progress, risks, and trade-offs.

Required qualifications, capabilities, and skills
  • 5+ years of experience or equivalent expertise in product management or a relevant domain area
  • 3+ years of owning complex data products or platforms where correctness, scale, and adoption are equally critical.
  • Demonstrated track record of shipping production products end-to-end, including roadmap ownership, backlog management, and measurable outcomes; experience delivering operationally supported platforms, not presentations.
  • Strong technical fluency across data platform fundamentals, including entity modeling, mastering and arbitration patterns, metadata and lineage, provenance, and data quality dimensions.
  • Ability to reason about algorithmic and operational trade-offs, including precision/recall, false positives/negatives, latency/throughput, and explainability versus automation, and to translate these into product decisions and success metrics.
  • Experience working with cross-functional teams across engineering, data engineering, applied machine learning, operations, and governance, with proven ability to influence in a matrixed environment.
  • Strong product operating discipline, including dependency management, release planning, clear requirements definition, and executive-level communication.

Preferred qualifications, capabilities, and skills
  • Demonstrated prior experience working in a highly matrixed, complex organization
  • Experience in financial services, particularly Corporate & Investment Banking, including exposure to enterprise data controls and audit expectations.
  • Prior experience with entity resolution or identity matching, deterministic rules frameworks, and machine learning-assisted matching or classification in high-volume environments.
  • Experience designing explainability, auditability, and human-in-the-loop governance patterns for AI-enabled production workflows.
  • Experience sourcing, normalizing, and integrating third-party data, including establishing scalable onboarding patterns and quality standards.
  • Familiarity with knowledge representation approaches such as knowledge graphs or ontology-driven modeling, particularly where downstream consumers require traceability and consistent semantics.

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

What JPMorgan Chase & Co. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom