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Data Science Research Jobs (NOW HIRING)

Applied Physics

Data Scientist

New York, NY · On-site

Assess the requirements for data science research from Applied Physics and the Advanced Propulsion Laboratory. * Engage with other developers frequently to share relevant knowledge, opinions, and ...

Applied Physics

Data Scientist

New York, NY · On-site

Assess the requirements for data science research from Applied Physics and the Advanced Propulsion Laboratory. * Engage with other developers frequently to share relevant knowledge, opinions, and ...

Applied Physics

Data Scientist

New York, NY

Assess the requirements for data science research from Applied Physics and the Advanced Propulsion Laboratory. * Engage with other developers frequently to share relevant knowledge, opinions, and ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Jobs for Humanity

Data Science Managers

Piscataway, NJ · On-site

Professor - Data Science - Tenured Department: Proteomics Salary: Open Posting Summary: Rutgers ... This role will involve directorship of the Research Collaboratory for Structural Bioinformatics ...

Elder Research

Data Analyst (Remote)

At least two (2) years of experience applied data science research or big data analytics. * Bachelor's Degree in Statistics, Applied Mathematics, Data Science, Computer Science, Operations Research ...

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How much do data science research jobs pay per year?

As of Jun 2, 2026, the average yearly pay for data science research in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Science Researcher, you need strong analytical skills, expertise in statistics and machine learning, and an advanced degree in a quantitative field such as computer science, mathematics, or engineering. Proficiency with programming languages like Python or R, data visualization tools, and experience using platforms such as TensorFlow or PyTorch is typically required. Curiosity, creativity, and clear communication are essential soft skills for designing research questions, interpreting results, and sharing findings with diverse audiences. These skills and qualities are crucial for driving innovative solutions and impactful insights in data-driven environments.

How does a Data Science Researcher typically collaborate with other departments within an organization?

Data Science Researchers frequently work cross-functionally, collaborating with teams such as engineering, product management, and business analytics. They often translate complex research findings into actionable insights, guiding product development or business strategies. Regular meetings, joint project planning, and code reviews are common, ensuring that research outcomes align with organizational goals. Effective communication and teamwork are key to integrating advanced data solutions into real-world applications.

What is data science research?

Data science research involves using scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Researchers in this field work on developing new data analysis techniques, machine learning models, and data-driven solutions to solve complex problems. The work often includes designing experiments, analyzing large datasets, and publishing findings to advance the understanding of data science methodologies.

What is the difference between Data Science Research vs Data Analyst?

AspectData Science ResearchData Analyst
CredentialsTypically requires advanced degrees (Master's or PhD) in Data Science, Statistics, or related fieldsOften requires a Bachelor's or Master's degree in Data Analysis, Statistics, or related areas
Work EnvironmentResearch labs, academic institutions, or R&D departments within companiesBusiness environments, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutions, tech companies focusing on innovationRetail, finance, healthcare, and other industries focusing on data-driven decision making

Data Science Research focuses on developing new algorithms, models, and theories, often in academic or R&D settings. In contrast, Data Analysts primarily interpret existing data to generate reports and insights for business decisions. Both roles require strong analytical skills but differ in scope, goals, and work environment.

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What job categories do people searching Data Science Research jobs look for? The top searched job categories for Data Science Research jobs are:
Data Science Research jobs near you

Senior Data Scientist (Boston)

TechStarsGroup

Boston, MA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

The Senior Data Scientist will play a pivotal role in providing programming, advanced statistical, and machine learning expertise to our Clinical Data Science team. This position is instrumental in supporting research initiatives focused on digital biomarkers and predictive model development within our innovative technology platform. The selected candidate will collaborate extensively with our dynamic team to fulfill analysis requirements as per our clients' needs. Responsibilities include leading data science projects related to digital biomarker discovery and patient behavior prediction. This encompasses exploratory data analysis, statistical analysis, development of inference models, creation of data visualizations, and ensuring data quality.

Essential Functions/Responsibilities:
  • Develop and implement high-quality code for digital biomarker analysis and inference models as application programming interfaces.
  • Conduct exploratory data analysis, statistical testing, and develop inference models to measure and validate novel digital biomarkers related to disease and behavior.
  • Create machine learning and statistical models to predict patient behavior, utilizing complex, high-dimensional data.
  • Engage in the assessment and implementation of computational and predictive analytics strategies to tackle research questions.
  • Play a key role in defining the experimental design and research scope, including data requirements, methodology, analysis, and validation strategies.
  • Independently manage experimental plans, analyze results, and report findings to leadership.
  • Produce data visualizations for a variety of data types, including complex digital biomarker data and model performance metrics.
  • Establish data quality metrics and conduct thorough data quality assessments.
  • Work closely with the applications research team to translate digital biomarkers and models into practical product applications.
  • Design and oversee continuous validation processes for systems incorporating digital biomarkers and predictive models.
  • Mentor junior staff and supervise student interns.
  • Communicate results to a broad audience, including clinical professionals, technical experts, and non-specialists.
  • Oversee client project portfolios, ensuring clear and effective communication across multiple initiatives.
  • Contribute to scientific publications, author abstracts, and present findings at professional gatherings.
Required Education & Training:
  • Masters degree, PhD, or equivalent in data science, machine learning, statistics, mathematics, informatics, or a related field.
  • At least 3 years of experience in complex data science, applied statistics, or machine learning projects.
  • Proficiency in Python for model development, including experience building Python libraries.
  • Familiarity with cloud computing environments such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).
  • Skilled in developing and validating machine learning models with standard algorithms (e.g., random forest, logistic regression, support vector machines).
  • Experience with statistical analysis and machine learning libraries (e.g., ScikitLearn, R).
  • Knowledge of statistical analysis methods.
  • Proficiency in ETL processes and SQL for data transformation.
  • Excellent communication skills, capable of explaining technical concepts to non-technical audiences.
  • Experience in scientific and technical writing.
  • A strong passion for science, research, and innovation in a team-based setting.
Preferred Qualifications:
  • Experience with deep learning libraries such as PyTorch or TensorFlow is highly desirable.
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