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Data Science Jobs in Hanover, NH (NOW HIRING)

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Data Science information

See Hanover, NH salary details

$37.4K

$122.5K

$196.2K

How much do data science jobs pay per year?

As of Jul 26, 2026, the average yearly pay for data science in Hanover, NH is $122,539.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $135,800.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Hanover, NH? The most popular types of Data Science jobs in Hanover, NH are:
What cities near Hanover, NH are hiring for Data Science jobs? Cities near Hanover, NH with the most Data Science job openings:
Infographic showing various Data Science job openings in Hanover, NH as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,539 per year, or $58.9 per hour.
Research Computing Consultant II - Data Science

Research Computing Consultant II - Data Science

Dartmouth College

Hanover, NH • On-site

Full-time

Posted 14 days ago


Dartmouth College rating

8.7

Company rating: 8.7 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

56th of 611 rated colleges and universities


Job description

Position Details
Position Information
Posting date
07/13/2026
Closing date
Open Until Filled
Yes
Position Number
1129656
Position Title
Research Computing Consultant II - Data Science
Hiring Range Minimum
$87,700
Hiring Range Maximum
$115,000
Union Type
Not a Union Position
SEIU Level
Not an SEIU Position
FLSA Status
Exempt
Employment Category
Regular Full Time
Scheduled Months per Year
12
Scheduled Hours per Week
40
Schedule
Location of Position
Hanover, NH
Remote Work Eligibility?
Hybrid
Is this a term position?
No
If yes, length of term in months.
NA
Is this a grant funded position?
No
Position Purpose
The Research Computing Consultant II (RCCII) - Data Science is a researcher-facing professional who partners with faculty, postdoctoral scholars, and graduate students to support data-intensive research across disciplines. This role applies expertise in applied statistics, artificial intelligence, and data science to help the campus research community, design rigorous analytical workflows, develop publication-quality visualizations, and build reproducible computational practices. The RCCII applies methodological knowledge across a broad range of research contexts, spanning biomedical and public health sciences through to the social sciences and humanities.
This is an early-career professional role designed for a curious individual with a foundational background and some experience in applied quantitative research support who is ready to develop their expertise within a collaborative, research-oriented environment. The position reports to the Director of Research Engagement and Data Science and works in close partnership with the Research Cyberinfrastructure and Research Software Engineering teams. Strong programming proficiency in R and Python, effective communication skills, workshop hosting experience, and a genuine enthusiasm for collaborative research are essential to success in this role.
Description
Dartmouth College seeks a research computing professional to serve as a computational thought partner to faculty and research teams across disciplines. This role sits at the intersection of applied data science, advanced computing, and collaborative research strategy.
The Research Computing Consultant II - Data Science advances Dartmouth's research mission by enabling scalable, reproducible, and innovative computational practices. This position partners directly with faculty, postdoctoral scholars, and graduate students to shape analytical approaches, optimize computational workflows, and expand adoption of advanced research technologies.
This role is within the Research Engagement and Data Science team, reporting to the Director of Research Engagement and Data Science and working in close collaboration with research computing infrastructure colleagues and campus partners.
Required Qualifications - Education and Yrs Exp
Master's degree
Required Qualifications - Skills, Knowledge and Abilities
  • Master's degree in biostatistics, statistics, data science, epidemiology, computer science, computational science, or a related quantitative discipline.
  • Minimum of one year of experience in applied data science, applied statistics, research computing, or computational research support.
  • Experience supporting or participating in data-intensive research projects.
  • Strong proficiency in both R and Python
  • Demonstrated experience with applied statistical modeling, including at minimum regression and mixed-effects frameworks.
  • Working knowledge of large language models or AI-assisted tools and their potential applications in research or data science contexts.
  • Familiarity with high-performance computing or advanced computational environments.
  • Demonstrated ability to communicate quantitative concepts clearly to audiences with diverse technical backgrounds.
  • Experience developing or delivering technical training, documentation, or instructional materials.
  • Ability to work on campus multiple days per week; this is a hybrid-eligible role requiring consistent in-person presence to support the research community.

Preferred Qualifications
  • Ph.D. in a quantitative discipline such as biostatistics, statistics, data science, epidemiology, or computational science.
  • Proficiency in SAS or Stata.
  • Strong data visualization skills, including experience developing interactive dashboards (e.g., Shiny, Dash, or comparable platforms).
  • Demonstrated ability to design, evaluate, or advise on AI-enabled workflows in academic or research settings, including critical assessment of appropriate use and limitations.
  • Working knowledge of Linux-based systems and workload scheduling tools (e.g., Slurm).
  • Background working with large-scale, high-dimensional, or sensitive datasets, including awareness of relevant regulatory and ethical considerations.
  • Exposure to research proposals or grant writing processes, including contribution to methods or computational sections.
  • Active or emerging engagement with scholarly communities through publications, conference presentations, or research working groups.
  • Grounding in research data management best practices and compliance considerations.

Department Contact for Recruitment Inquiries
Christian Darabos
Department Contact Phone Number
Christian.Darabos@dartmouth.edu
Department Contact for Cover Letter and Title
Christian Darabos, Sr. Director, Research Computing and Data (RCD)
Department Contact's Phone Number
Equal Opportunity Employer
Dartmouth College is an equal opportunity employer under federal law. We prohibit discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications are welcome from all.
Background Check
Employment in this position is contingent upon consent to and successful completion of a pre-employment background check, which may include a criminal background check, reference checks, verification of work history, conduct review, and verification of any required academic credentials, licenses, and/or certifications, with results acceptable to Dartmouth College. A criminal conviction will not automatically disqualify an applicant from employment. Background check information will be used in a confidential, non-discriminatory manner consistent with state and federal law.
Is driving a vehicle (e.g. Dartmouth vehicle or off road vehicle, rental car, personal car) an essential function of this job?
Not an essential function
Special Instructions to Applicants
Dartmouth College has a Tobacco-Free Policy. Smoking and the use of tobacco-based products (including smokeless tobacco) are prohibited in all facilities, grounds, vehicles or other areas owned, operated or occupied by Dartmouth College with no exceptions. For details, please see our policy. https://policies.dartmouth.edu/policy/tobacco-free-policy
Additional Instructions
Quick Link
https://searchjobs.dartmouth.edu/postings/86523
Key Accountabilities
Description
Researcher Consultation and Data Science Support -
  • Assists faculty, postdoctoral scholars, and graduate students in assessing analytic needs and identifying appropriate quantitative, statistical, and computational approaches suited to their research questions and disciplinary context.
  • Provides foundational guidance on model selection, validation strategies, and interpretation of analytical results across diverse research domains including biomedicine, public health, social sciences, and the humanities.
  • Guides researchers in evaluating and responsibly adopting AI-enabled tools, including large language models, to enhance their analytical workflows and research practice.
  • Assists researchers in structuring, cleaning, and summarizing complex datasets to support exploratory analysis, reporting, and communication of findings.
  • Supports implementation of commonly used statistical analyses including regression, mixed-effects, survival, and multivariate approaches using R and Python.
  • Contributes to the preparation of methods sections, analytical summaries, and data narratives for research manuscripts and proposals.
  • Assists with study design discussions and supports analytical planning related to research proposals.
  • Helps develop text and corpus analysis workflows, including data extraction, preprocessing, and quantitative characterization of textual or qualitative data sources.
  • Assists project teams in developing reproducible workflows using scripting, version control, and workflow management best practices.
  • Troubleshoots routine analytical and methodological challenges, and works closely with senior team members to resolve more complex problems.

Percentage Of Time
40
Description
HPC, Cloud, and AI Workflow Enablement -
  • Assists researchers in effectively using Dartmouth's high-performance computing environments and cloud-based research platforms including job submission, monitoring, and basic troubleshooting.
  • Collaborates with the Research Cyberinfrastructure and Research Software Engineering colleagues to communicate user needs and improve the research computing experience.
  • Helps academic partners evaluate and appropriately use AI-enabled tools within data science and outreach workflows.

Percentage Of Time
15
Description
Outreach, Education, and Research Computing Adoption -
  • Assists in the design and delivery of introductory workshops and training sessions on applied statistics, data science methods, data visualization, artificial intelligence, reproducible research practices, and HPC usage.
  • Develops accessible documentation, tutorials, and practical learning resources for researchers at all career stages.
  • Provides accessible consultation and training support.
  • Engages departments and interdisciplinary research groups to expand awareness and adoption of research computing and data science services.
  • Translates complex statistical and computational concepts into clear, accessible guidance for audiences with diverse technical backgrounds.

Percentage Of Time
25
Description
Data Management, Visualization, and Research Lifecycle Support -
  • Develops publication-quality data visualizations using R, Python, or comparable tools, with attention to accessibility and clarity.
  • Supports development of interactive dashboards and reporting tools to help researchers communicate findings effectively (e.g., Shiny, Dash, or comparable platforms).
  • Advises investigators on data organization, storage strategies, and lifecycle management practices appropriate to their discipline and compliance requirements.
  • Provides guidance on responsible and compliant use of data science and AI tools in research contexts.
  • Promotes documentation and reproducibility as foundational practices across research projects.

Percentage Of Time
20
Description
Professional Development and Institutional Contribution -
  • Maintains and actively expands knowledge of applied statistical methods, data science methodologies, research computing technologies, and emerging developments in AI as they apply to research practice.
  • Serves as a collegial resource to team members and contributes to a collaborative, service-oriented environment.
  • Promotes equitable and inclusive access to research computing resources, statistical consultation, and training across campus communities.

Percentage Of Time
--
Demonstrates professionalism and collegiality through actions, interactions, and communications with others appropriate to an environment that is welcoming to all.
--
Performs other duties as assigned.

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