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Mechanical Data Science Jobs (NOW HIRING)

Envision

Data Scientist

Manhattan, NY · Remote

Required qualifications Masters + 1+ years, or a PhD in Data Science, Computer Science, Applied ... Solid comprehension of the mechanisms behind widely used AI/ML algorithms - including their ...

Merck & Co.

Core to the Data, AI, and Genome Sciences (DAGS) function is an AI/ML-first approach to improving target and biomarker discovery, validation, and selection, and elucidating complex disease mechanisms.

Vantage Data Centers

Data Scientist, NA

Denver, CO · On-site

Essential Job Functions Data Science Strategy & Model Development * Develop predictive and ... Evaluate model performance and implement continuous improvement mechanisms. * Result: High-impact ...

Mercor

Data Scientist | Upto $100/hr

New York, NY · Remote

$100/hr

... Science , Statistics , Biology , Electrical/Mechanical/Civil Engineering , Physics , Chemistry , Mathematics , Materials Science , or other STEM background. * Demonstrated technical expertise in ...

Westrock

Sr. Anlst, Data Science & Eng

Atlanta, GA · On-site +1

$82K - $104K/yr

... based mechanisms, batch and real-time processing. * Develop EDI maps and set up new Trading ... Data Science and Engineering Analyst-related occupation. Position requires five (5) years of ...

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Mechanical Data Science information

How does a Mechanical Data Scientist typically collaborate with engineering teams during product development?

Mechanical Data Scientists often work closely with mechanical engineers, product designers, and manufacturing teams to analyze sensor data, optimize processes, and predict system performance. They translate complex datasets into actionable insights, helping engineering teams make informed decisions about material selection, design iterations, and maintenance schedules. Regular collaboration involves cross-functional meetings, joint problem-solving sessions, and sharing data-driven recommendations to improve product reliability and efficiency. This multidisciplinary teamwork is key to integrating advanced analytics into the mechanical engineering workflow.

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

AspectMechanical Data ScienceMechanical Engineering
Required CredentialsTypically requires a degree in Data Science, Computer Science, or related fields, with knowledge of programming and data analysisRequires a degree in Mechanical Engineering, with emphasis on design, thermodynamics, and materials
Work EnvironmentPrimarily in data analysis labs, software development, or research settings involving large datasetsIn manufacturing, design offices, or research labs focused on physical systems and product development
Industry UsageUsed in predictive maintenance, simulation, and optimization within manufacturing and product designApplied in product design, system analysis, and manufacturing processes

Mechanical Data Science focuses on analyzing and interpreting data related to mechanical systems, often involving programming and statistical skills. Mechanical Engineering centers on designing, analyzing, and manufacturing mechanical systems. While both fields overlap in industry and problem-solving, their core skills and daily tasks differ significantly.

What are the key skills and qualifications needed to thrive as a Mechanical Data Scientist, and why are they important?

To thrive as a Mechanical Data Scientist, you need a solid background in mechanical engineering principles, data analysis, and statistical modeling, often supported by a degree in engineering or data science. Proficiency with programming languages like Python or MATLAB, familiarity with machine learning frameworks, and experience using simulation and CAD tools are commonly required. Strong problem-solving abilities, effective communication, and interdisciplinary collaboration make candidates stand out in this role. These skills and qualities are crucial for leveraging data insights to optimize mechanical systems and drive innovation in engineering projects.

What is Mechanical Data Science?

Mechanical Data Science is an interdisciplinary field that combines mechanical engineering principles with data science techniques to analyze, model, and optimize mechanical systems and processes. Professionals in this area use data-driven methods, such as machine learning and statistical analysis, to improve the design, operation, and maintenance of mechanical equipment. This can include applications in manufacturing, robotics, automotive engineering, and predictive maintenance. Mechanical Data Scientists often work with large datasets collected from sensors and machines to uncover insights that drive efficiency and innovation.
Infographic showing various Mechanical Data Science job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, 11% Temporary, and 22% Contract. Highlights an 100% In-person job distribution.
Data Scientist - Washington, DC

Data Scientist - Washington, DC

Veteran Jobs - 2023 Mar 01 - Veterans Resources

Washington, DC

$125K - $155K/yr

Other

Posted 23 days ago

Job description

PotomacWave is looking for a Data Scientist to join our team supporting a Federal client in Washington, DC. This position will support the Office of Intelligence and Counterintelligence. This role will lead the development and implementation of advanced data science algorithms, machine learning models, and sophisticated data visualizations to solve complex analytic challenges for the mission, with a particular focus on improving data comprehension and driving data-driven decision-making processes.
Responsibilities:
  • Lead efforts to process large structured and unstructured datasets, developing and operationalizing data models, advanced analytic tools, and applications that optimize decision-making and enhance analytic throughput.
  • Design and implement advanced data collection, mining, clustering analysis, pattern recognition, and trends analysis techniques to develop actionable intelligence and inform strategic decisions.
  • Collaborate closely with analysts to build robust prototypes, prove complex concepts, and facilitate the widespread adoption of cutting-edge data science technologies and methodologies within the office.
  • Champion enterprise innovation, significantly increasing data awareness, and demonstrate the transformative value of advanced analytics and data visualization.
  • Stay abreast of bleeding-edge technology standards, industry trends, emerging technologies, and software development best practices, incorporating them into actionable strategies.
  • Architect and leverage advanced technologies including Python, R, AWS, Java, SQL, Tableau, D3JS, and Spark to analyze high volumes of data, reveal hidden patterns, and create compelling data narratives.
  • Lead the design and build of complex algorithms and machine learning models throughout the entire development lifecycle, ensuring scalability and operational effectiveness.
  • Evaluate and recommend advanced training opportunities, fostering a culture of continuous learning and skill development within the team.
  • Develop and codify structured processes for data-driven decision-making, leading initiatives to improve readership, feedback mechanisms, and overall analytic throughput.
  • Significantly contributes to the data science community by advocating for strategic data-driven quality projects and advanced process improvements.
  • Partner with cross-functional teams to meticulously document complex requirements, strategically leverage existing capabilities, and deliver high-impact products to customers.
  • Combine rigorous scientific method, advanced mathematics, statistics, specialized programming, and compelling storytelling to uncover deeply actionable insights and communicate them effectively.
  • Review mission needs, leading the evaluation of policy and program effectiveness through a data-centric lens.
  • Lead participation in enterprise-wide data science projects involving highly innovative approaches where precedents may not exist, setting new standards for the organization.
Qualifications:
  • A bachelor's degree in the following is required: data science, computer science, information science, mathematics, or statistics. A master's degree is preferred.
  • A professional certification in data science is required.
  • A minimum of four (4) years of experience in a data science related field.
  • The selection of an individual for this position may be conditioned upon their successful completion of a counterintelligence-scope polygraph examination.
  • Must be a U.S. Citizen and have an active DOE Q or Top-Secret clearance.

Salary range $125,000 - $155,000
To apply for this position, please go to: https://potomacwaveconsulting.applytojob.com/apply/SySDcwP3mc/Data-Scientist?source=VetJobs


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