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Applied Math Jobs in Philadelphia, PA (NOW HIRING)

Software Engineer

Camden, NJ · On-site

$75/hr

Demonstrated analytical, applied mathematics and problem-solving skills * Strong written and oral communication skills * Strong technical documentation skills * Active Secret or higher Clearance.

Showing results 21-40

Applied Math information

See Philadelphia, PA salary details

$22.7K

$59.4K

$95.4K

How much do applied math jobs pay per year?

As of Aug 7, 2026, the average yearly pay for applied math in Philadelphia, PA is $59,372.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,400.00 and $70,600.00 per year, depending on experience, location, and employer.

Is applied math a useful degree?

Applied math is a useful degree for careers in data analysis, finance, engineering, and research, as it develops skills in problem-solving, modeling, and quantitative analysis. Graduates often find employment in industries that rely on mathematical and computational tools, and the degree can lead to roles requiring programming and statistical knowledge.

What jobs can you get with applied math?

Applied math graduates can pursue careers such as data analyst, operations researcher, financial analyst, actuary, or software developer. These roles often require strong analytical skills, proficiency in programming languages like Python or R, and knowledge of statistical and mathematical modeling. Many positions are found in finance, technology, healthcare, and government sectors.

What is an applied mathematician?

Applied mathematicians are professionals who use mathematical theories, techniques, and computational methods to solve practical problems in fields such as engineering, science, business, and industry. They often develop models to analyze real-world phenomena, optimize processes, and predict outcomes. Applied mathematicians may work in diverse areas like data analysis, operations research, finance, and computer science, collaborating with experts from other disciplines to address complex challenges.

Is applied math in demand?

Applied math professionals are in high demand across industries such as finance, data analysis, engineering, and technology due to their skills in modeling, problem-solving, and quantitative analysis. Employers seek candidates with strong analytical abilities and proficiency in tools like MATLAB, Python, or R, making applied math a valuable and often well-compensated field.

What is the difference between Applied Math vs Data Analyst?

AspectApplied MathData Analyst
Required CredentialsBachelor's or higher in Mathematics, Applied Math, or related fieldsBachelor's or higher in Statistics, Data Science, or related fields
Work EnvironmentResearch labs, academia, finance, engineeringBusiness, finance, healthcare, marketing
Industry UsageModeling, simulations, algorithm developmentData interpretation, reporting, visualization
Common Search/ComparisonApplied Math vs Data Analyst

Applied Math and Data Analysts often share skills in statistical analysis and problem-solving. However, Applied Math focuses more on developing mathematical models and algorithms, while Data Analysts primarily interpret and visualize data to inform business decisions. Both roles are vital across industries, but their daily tasks and focus areas differ significantly.

What careers use applied math?

Applied math is used in careers such as data analyst, financial analyst, operations researcher, actuary, engineer, and computer scientist. These roles involve using mathematical models, statistical techniques, and computational tools to solve real-world problems across industries like finance, technology, healthcare, and engineering.

What are some typical projects or problems an applied mathematician may work on within a multidisciplinary team?

Applied mathematicians often collaborate with experts from fields such as engineering, computer science, and finance to tackle real-world challenges. For example, they might develop algorithms for optimizing logistics and supply chains, create mathematical models to predict disease spread in healthcare, or analyze large data sets to inform business strategies. This collaboration typically involves regular meetings, data sharing, and iterative problem solving, making strong communication skills and adaptability essential for success in the role.

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

To thrive as an Applied Mathematician, you need strong mathematical modeling, analytical, and problem-solving skills, usually supported by a degree in mathematics, applied mathematics, or a related field. Familiarity with programming languages (such as Python, MATLAB, or R), statistical software, and computational tools is typically required. Excellent communication, teamwork, and critical thinking abilities help translate complex mathematical concepts for diverse audiences and collaborative projects. These skills are vital for developing solutions to real-world problems across industries, ensuring accuracy, innovation, and practical impact.
What are popular job titles related to Applied Math jobs in Philadelphia, PA? For Applied Math jobs in Philadelphia, PA, the most frequently searched job titles are:
What cities near Philadelphia, PA are hiring for Applied Math jobs? Cities near Philadelphia, PA with the most Applied Math job openings:
Infographic showing various Applied Math job openings in Philadelphia, PA as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 97% Physical, and 3% Remote job distribution, with an average salary of $59,372 per year, or $28.5 per hour.

Head of Applied AI Research & Development

Vanguard

Malvern, PA

Full-time

Posted 7 days ago


Job description

Lead with purpose and keep growing. See your future here. Vanguard’s Enterprise AI & Research (EAiR) team is advancing the next generation of AI capabilities by transforming cutting-edge research into enterprise-scale products that create measurable value across the organization. The Head of Applied AI Research & Development leads the translation of frontier AI innovations into scalable platforms, intelligent systems, and production-ready capabilities that accelerate Vanguard’s strategic objectives. This organization works across emerging areas including Generative AI, Agentic AI, World Models and Large World Models (LWMs), Cognitive AI Architectures, Responsible AI, Knowledge Systems, and next-generation reasoning systems.

Role Overview
The Head of Applied AI Research &Development serves as the strategic leader responsible for operationalizing advanced AI research into enterprise-ready capabilities. This leader oversees multidisciplinary teams of applied AI/ML researchers, machine learning engineers, and AI platform specialists focused on delivering scalable AI solutions that directly impact Vanguard’s products, operations, and client experience.
The role combines technical leadership, product strategy, and organizational influence to accelerate AI adoption across the enterprise. Working closely with AI Research, AI Product, Engineering, Data, and business organizations, this leader establishes the frameworks, methodologies, and delivery mechanisms required to transform novel AI techniques into robust enterprise capabilities.
Success in this role requires balancing long-term innovation with near-term execution while building reusable AI platforms that continuously improve through enterprise knowledge, evolving data, and organizational learning.
Core Responsibilities

  • Define and execute Vanguard’s Applied AI R&D strategy, aligning investments in applied AI, frontier research, and enterprise AI capabilities with long-term business objectives and competitive differentiation.
  • Drive innovation across frontier AI domains, including foundation models, Large World Models (LWMs), world modeling systems, agentic AI, enterprise reasoning, cognitive AI architectures, and next-generation intelligent systems.
  • Direct the development of applied AI architectures and research capabilities supporting reasoning, planning, simulation, knowledge representation, memory-aware intelligence, adaptive decision-making, and continuously evolving world-state models.
  • Establish applied AI methodologies, standards, and evaluation frameworks that ensure AI systems are secure, governed, trustworthy, scalable, and capable of continuous improvement through enterprise data, feedback loops, and organizational learning.
  • Partner with business, product, engineering, and external research organizations to accelerate adoption of AI capabilities, proof of concepts, build strategic partnerships, and translate emerging research into measurable business value.
  • Lead multidisciplinary AI research, engineering, and platform teams responsible for translating advanced research into scalable, production-grade AI systems, products, and enterprise capabilities.
  • Build and develop a world-class Applied AI organization by recruiting, mentoring, and growing high-performing talent while fostering a culture of technical excellence, experimentation, innovation, and responsible AI development.

Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Electrical Engineering, Cognitive Science, Management Science or a related discipline.
-  7+ years of experience leading Applied AI, Machine Learning, AI Engineering, or AI Platform teams within industry or research environments.
- Proven experience delivering applied AI capabilities which are repeatable across research or industry settings
- Deep expertise in large language models, foundation models, agentic AI, machine learning systems, reinforcement learning, retrieval systems, reasoning architectures, knowledge representation, or advanced AI applications.
- Experience designing AI systems capable of contextual understanding, sequential reasoning, adaptive decision-making, memory-aware architectures, or complex workflow orchestration
- Strong understanding of modern AI development lifecycles including experimentation, evaluation, deployment, monitoring, and continuous improvement
- Experience building enterprise AI solutions, model governance processes, evaluation frameworks, and scalable ML models
- Hands-on expertise with modern ML frameworks including PyTorch, TensorFlow, Hugging Face, distributed training, and cloud AI platforms
-Demonstrated ability to lead large, multidisciplinary AI initiatives spanning research, academic, business organizations across both industry or research environments

- Exceptional executive communication skills with experience influencing senior leadership and enterprise strategy

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.