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Applied Science Engineering Jobs in New York (NOW HIRING)

Review Applied Science work at the highest level across the company, ensuring the methods used ... Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant ...

Review Applied Science work at the highest level across the company, ensuring the methods used ... Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant ...

Review Applied Science work at the highest level across the company, ensuring the methods used ... Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant ...

Staff Applied Scientist

New York, NY ยท On-site

$260K - $382K/yr

About the role We are seeking an exceptional Staff Applied Researcher to join our Applied Science ... Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant ...

Review applied science work at the highest level across the company, ensuring the methods used ... Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant ...

Review applied science work at the highest level across the company, ensuring the methods used ... Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant ...

... and engineering best practices. You will develop reusable science components and services that ... As an Applied Scientist, you will... - Understand use cases across the business and adopt/extend ...

Showing results 21-40

Applied Science Engineering information

See New York salary details

$44.3K

$108K

$171.2K

How much do applied science engineering jobs pay per year?

As of Aug 21, 2026, the average yearly pay for applied science engineering in New York is $108,045.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $126,900.00 per year, depending on experience, location, and employer.

What is applied science engineering?

Applied science engineering is a multidisciplinary field that uses scientific knowledge and engineering principles to develop practical solutions for real-world problems. Professionals in this area bridge the gap between theoretical research and its practical application, working on projects that can range from developing new materials and medical devices to improving environmental systems. They often collaborate with scientists, engineers, and business leaders to translate discoveries into tangible products or processes. Their work can be found in industries such as biotechnology, manufacturing, information technology, and energy.

What are the key skills and qualifications needed to thrive as an applied science engineer?

To thrive as an Applied Science Engineer, you need a strong background in mathematics, physics, and engineering principles, typically supported by a degree in engineering or a related science field. Experience with programming languages (such as Python or MATLAB), data analysis tools, and relevant certifications in areas like machine learning or computational modeling are commonly required. Strong problem-solving abilities, teamwork, and effective communication skills help you collaborate and convey complex technical concepts. These skills ensure innovative solutions, accurate analyses, and successful project outcomes in a multidisciplinary engineering environment.

How do applied science engineers typically collaborate with cross-functional teams during the development of new technologies?

Applied Science Engineers often work closely with product managers, data scientists, and software developers to bridge the gap between scientific research and practical implementation. They contribute their expertise by designing experiments, analyzing data, and translating research findings into scalable solutions. Regular meetings, collaborative brainstorming sessions, and shared project management tools are common, ensuring alignment between scientific objectives and business goals. This collaborative structure not only accelerates innovation but also provides engineers with exposure to diverse perspectives and continuous learning opportunities.

What is the difference between Applied Science Engineering vs Mechanical Engineering?

AspectApplied Science EngineeringMechanical Engineering
Required CredentialsBachelor's or higher in applied science, engineering, or related fieldsBachelor's or higher in mechanical engineering or related disciplines
Work EnvironmentResearch labs, product development, testing facilitiesManufacturing plants, design offices, testing labs
Employer & Industry UsageTech companies, research institutions, manufacturing firmsAutomotive, aerospace, energy, manufacturing industries
Common Search & Comparison IntentUnderstanding career paths, job roles, and skillsDesign, analysis, and manufacturing processes

Applied Science Engineering focuses on applying scientific principles to develop new technologies and solutions, often emphasizing research and development. Mechanical Engineering, on the other hand, centers on designing and manufacturing mechanical systems. Both roles require similar educational backgrounds and are used across various industries, but their primary focus and work environments differ.

Is an applied science engineering degree worth it?

An applied science engineering degree provides practical skills in areas like data analysis, programming, and technical problem-solving, which are valuable in industries such as manufacturing, technology, and research. It can lead to roles that require hands-on technical expertise and often offers good job prospects and salary potential, especially when combined with relevant certifications or experience.

What can you do with a degree of applied science?

Applied Science Engineering graduates can work in research and development, product design, manufacturing, and technical consulting across industries such as aerospace, automotive, electronics, and energy. They often utilize skills in data analysis, problem-solving, and engineering tools like CAD software, and may pursue certifications to enhance career opportunities.

What are popular job titles related to Applied Science Engineering jobs in New York?

For Applied Science Engineering jobs in New York, the most frequently searched job titles are:

What job categories do people searching Applied Science Engineering jobs in New York look for?

The top searched job categories for Applied Science Engineering jobs in New York are:

Infographic showing various Applied Science Engineering job openings in New York as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, 3% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $108,045 per year, or $51.9 per hour.

Staff Applied Scientist

Garner Health

New York, NY โ€ข Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 5 days ago


Job description

About the role:

We are seeking an exceptional Staff Applied Scientist to join our Applied Science team. Garner is hiring Applied Scientists to design and ship the algorithmic systems at the core of our product. Our members rely on us to answer hard questions - Which doctor should I see? What will it cost? When should we reach out, and how? - and the quality of those answers is determined by the algorithms behind them.

This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund.

This is a player-coach role. You will be a hands-on-keys Applied Scientist, while also leading a small team that helps you deliver on your roadmap. Your time will be split between your own technical work and working with your team to shape how they approach their problems. This role is a good fit for someone who wants to develop their management toolkit while continuing to work closely on their own technical work, and it can lead either towards management or a deeper senior IC track.

Where you will work:

This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday.

What you will do:
  • Own the most ambiguous, high-stakes problems facing the company end-to-end, and set how the team frames and approaches them
  • Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks
  • Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship
  • Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for, and set the standard for how the team selects and applies these approaches
  • Deliver algorithmic breakthroughs that move the company's most important metrics, pioneering approaches that become how applied science is done at Garner
  • Lead a small team - set their technical direction, unblock them when they're stuck, and share accountability for their growth and the quality of what they ship
  • Review Applied Science work at the highest level across the company, ensuring the methods used across teams are sound and correctly applied
  • Build a deep understanding of the healthcare economy and Garner's place in it

To make the role concrete, here are three problems on our near-term roadmap:

  • Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions.
  • AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely.
  • Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint - SMS, push, phone, or email - to influence member behavior toward better-quality, lower-cost care.
The ideal candidate has:
  • 6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant advanced degree, PhDs preferred
  • A bias toward action, quickly translating ideas into working prototypes to test approaches
  • Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them
  • Recognized technical authority, with the judgment to ensure the techniques used across an organization are sound
  • Strong interest in mentoring or technically leading other Scientists - formal management experience is welcome, but not required
  • Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem
  • Strong communication skills, including at the executive level, with a track record of driving alignment across an organization
  • A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback
What you'll get here

You'll work on problems that matter, at a company working to change healthcare at scale. You'll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission.

At Garner, you'll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It's demanding by design. You'll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose.

Technologies we use:
  • Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume - bring your judgment.

This is a unique opportunity to work on high-impact problems in healthcare - shaping how members find better care through algorithmic systems that directly influence healthcare outcomes, and helping the scientists around you do the same.

Compensation Transparency:

The target base comp range for this position is $300,000-$390,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more.