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Algorithmic Execution Quant Jobs in Boston, MA (NOW HIRING)

Senior Product Marketing Manager

Boston, MA ยท Remote

$131K - $172K/yr

Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker ... execution. You will be driving how Beacon positions and communicates its solutions to decision ...

Senior Product Marketing Manager

Boston, MA ยท On-site +1

$131K - $172K/yr

Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker ... execution. You will be driving how Beacon positions and communicates its solutions to decision ...

Senior Product Marketing Manager

Boston, MA ยท On-site

$131K - $172K/yr

Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker ... execution. You will be driving how Beacon positions and communicates its solutions to decision ...

Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker ... Support financial performance monitoring activities (e.g., execution against forecast) * Support ...

Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker ... Support financial performance monitoring activities (e.g., execution against forecast) * Support ...

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Showing results 1-20

Algorithmic Execution Quant information

See Boston, MA salary details

$57K

$129.5K

$213.5K

How much do algorithmic execution quant jobs pay per year?

As of Jul 5, 2026, the average yearly pay for algorithmic execution quant in Boston, MA is $129,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $165,700.00 per year, depending on experience, location, and employer.

What is the difference between Algorithmic Execution Quant vs Quantitative Trader?

AspectAlgorithmic Execution QuantQuantitative Trader
Primary FocusDeveloping and implementing algorithms for trade execution to minimize market impactCreating trading strategies to generate alpha and profit from market movements
Work EnvironmentQuantitative research teams, trading desks, technology-drivenTrading floors, portfolio management teams, research departments
Required SkillsProgramming, market microstructure, execution algorithmsQuantitative modeling, market analysis, strategy development

While both roles involve quantitative skills, an Algorithmic Execution Quant specializes in optimizing trade execution processes, whereas a Quantitative Trader focuses on developing strategies to generate profits. The roles often collaborate but serve different functions within trading firms.

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

To thrive as an Algorithmic Execution Quant, you need a strong background in quantitative analysis, programming (often in Python or C++), and a solid understanding of financial markets, typically supported by an advanced degree in a quantitative discipline. Proficiency with statistical modeling tools, trading platforms, and market data systems, as well as familiarity with technologies like FIX protocol, is crucial. Strong problem-solving ability, attention to detail, and effective communication help you collaborate across trading, research, and technology teams. These skills are essential for designing, optimizing, and maintaining robust trading algorithms that achieve best execution and mitigate risk in fast-moving markets.

What are some common challenges faced by Algorithmic Execution Quants when developing and deploying trading algorithms?

Algorithmic Execution Quants often encounter challenges such as adapting strategies to rapidly changing market conditions, managing latency and slippage, and ensuring compliance with regulatory requirements. They must also balance the need for innovation with the necessity for robust risk controls and system reliability. Collaboration with traders, developers, and risk managers is essential to refine algorithms and ensure they perform optimally in live trading environments.

What does an Algorithmic Execution Quant do?

An Algorithmic Execution Quant is responsible for designing, developing, and optimizing algorithms that execute large financial trades efficiently and at minimal cost. They analyze market microstructure, create models to predict market impact, and work closely with traders and engineers to implement these strategies in real-time trading systems. Their work is essential in minimizing transaction costs and improving trade execution quality for their firm.
What are popular job titles related to Algorithmic Execution Quant jobs in Boston, MA? For Algorithmic Execution Quant jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Algorithmic Execution Quant jobs in Boston, MA look for? The top searched job categories for Algorithmic Execution Quant jobs in Boston, MA are:
What cities near Boston, MA are hiring for Algorithmic Execution Quant jobs? Cities near Boston, MA with the most Algorithmic Execution Quant job openings:

Head of Digital Health Data and Evidence

Takeda

Boston, MA โ€ข On-site

Full-time

Dental, Vision, Life, Retirement, PTO

Posted 26 days ago


Job description

By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

Head of Digital Health Data and Evidence

OBJECTIVES/PURPOSE

The Head of Digital Health Data and Evidence is pivotal in shaping and executing the evidence generation, data strategy, and analytics agenda across Takeda's global digital health portfolio. This role ensures that Takeda's digital health products, patient services, and data assets are underpinned by robust evidence frameworks, scalable data architectures, and AI-enabled capabilities that drive measurable business and patient impact. The role also leads a global Digital Health Data & Evidence team, building organizational capability and representing the function in senior governance forums. The objectives of this role include:

  • Define and deliver end-to-end evidence frameworks and data strategies across the digital health portfolio, including patient services and CRM-derived data assets.
  • Establish and oversee data governance, privacy, and interoperability standards for patient-domain data, including industry standards such as FHIR and OMOP, and integration with EMRs and disease registries.
  • Drive the development of data-driven products, predictive models, and AI-enabled tools that support patient identification, clinical decision support, and digital health solution scalability.
  • Lead market access data strategy, managing third-party pricing intelligence platforms and driving automation of tender pricing and market access decision-support tools.
  • Build, lead, and develop a high-performing global team, fostering cross-functional collaboration and representing the function in Core Team and Steering Committee governance forums.
  • Translate business and clinical needs into deployable, scalable data and evidence solutions in partnership with R&D, Quantitative Sciences, Global Evidence & Outcomes, and technical engineering teams.
  • Position evidence and data as core enablers of digital health commercialization, reimbursement, and patient outcomes.

ACCOUNTABILITIES

  • Define, communicate, and execute the global evidence generation and data strategy across the digital health product and services portfolio.
  • Develop and govern end-to-end data strategies spanning digital therapeutics, digital companion products, patient support program data, and CRM-derived patient datasets.
  • Oversee data governance for patient-domain data, ensuring privacy, compliance, and adherence to internal and external regulatory standards.
  • Lead interoperability initiatives, including the design and execution of proofs-of-concept and production deployments using industry standards (e.g., FHIR, OMOP), and integration with EMRs and disease registries.
  • Direct the development of data products and algorithms, including patient identification models, predictive analytics, and AI-enabled clinical and operational tools.
  • Translate business, clinical, and operational requirements into scalable, deployable data and analytics solutions in partnership with engineering, R&D, Quantitative Sciences, and Global Evidence & Outcomes.
  • Manage external market access intelligence platforms to deliver continuous pricing, tender, and market access insights through reports and interactive dashboards.
  • Lead the automation and AI-enablement of market access decision-support capabilities, including tender pricing tools.
  • Lead the global Digital Health Data & Evidence Hub, including team structure, hiring, performance management, and career development of direct reports.
  • Drive team capability uplift through targeted training and certification programs (e.g., FHIR), internal tooling, and AI-powered enablement assets such as guided chatbots.
  • Coach team members through stretch assignments and provide mentorship that supports both individual growth and organizational succession.
  • Represent the Digital Health Data and Evidence function in Core Team meetings, Steering Committees, and other senior governance forums.
  • Partner with external stakeholders-academic institutions, technology vendors, data providers, healthcare providers, and research organizations-to advance evidence generation and data interoperability objectives.
  • Drive evidence and data initiatives to completion within agreed timelines, managing scope, risks, dependencies, and stakeholder alignment.
  • Communicate findings, strategies, and recommendations clearly to internal and external audiences, including senior leadership.
  • Continuously evolve evidence generation and data methodologies in line with industry trends and best practices.

DIMENSIONS AND ASPECTS

Technical/Functional (Line) Expertise

  • Deep expertise in evidence generation methodologies for digital health products, including clinical, real-world, and economic evidence.
  • Strong command of healthcare data standards and interoperability frameworks, including FHIR, OMOP, and EMR/registry integration.
  • Proven experience designing and overseeing end-to-end data strategies, including data governance, privacy, and patient-domain data management.
  • Working knowledge of AI/ML, predictive modelling, and the development of data-driven products in a regulated healthcare environment.
  • Familiarity with market access, drug pricing, and tender intelligence platforms, including the use of analytics and automation to drive decision-making.
  • Understanding of digital health regulatory and reimbursement environments across multiple geographies.

Leadership (Vision, strategy and business alignment, people management, communication, influencing others, managing change)

  • Ability to define and articulate a clear, ambitious vision for digital health data and evidence and translate it into actionable strategy.
  • Demonstrated experience leading and developing global, cross-functional teams in a matrixed environment.
  • Strong people leadership skills, including coaching, performance management, and capability building through stretch assignments.
  • Skilled in influencing stakeholders across business, technical, and clinical domains, and at multiple levels of seniority.
  • Excellent written and oral communication skills, with the ability to translate complex technical and scientific content for executive and non-technical audiences.
  • Experience leading change and driving adoption of new methodologies, tools, and ways of working.

Decision-making and Autonomy

  • Ability to make autonomous, high-impact decisions on data strategy, evidence priorities, and investment trade-offs.
  • Strong problem-solving capability, balancing scientific rigor, technical feasibility, and commercial pragmatism.
  • Ability to navigate ambiguity, prioritize across a broad portfolio, and align competing stakeholder interests toward shared outcomes.

Interaction

  • Builds and sustains strong working relationships with senior business leaders, Digital, Data & Technology counterparts, R&D, Medical, and Commercial functions.
  • Acts as a trusted advisor on evidence, data, and analytics matters in Core Team and Steering Committee forums.
  • Maintains effective partnerships with external vendors, academic and research institutions, healthcare systems, and technology providers.
  • Fosters alignment across global, regional, and local stakeholders.

Innovation

  • Functions as a thought leader for digital health data, evidence, and AI, bringing external perspective into the organization.
  • Champions the adoption of emerging standards (e.g., FHIR, OMOP), AI-enabled tools, and novel evidence approaches.
  • Cultivates a culture of experimentation and continuous improvement within the team and across collaborating functions.

Complexity

  • Operates across a complex, global digital health portfolio spanning multiple therapeutic areas, product types, and stages of maturity.
  • Integrates evidence and data activities with product development, commercialization, market access, and patient services strategies.
  • Navigates multi-jurisdictional regulatory, privacy, and reimbursement environments.
  • Balances long-horizon strategic initiatives (e.g., interoperability, data governance) with near-term delivery commitments (e.g., tender support, dashboards, evidence dossiers).

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

Boston, MA

U.S. Base Salary Range:

$177,000.00 - $278,080.00


The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job.The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location.

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

LocationsBoston, MAWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull time

Job Exempt

YesIt is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.