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Data Analyst Data Science Jobs in White River Junction, VT

Munich Re

Data and AI Enterprise Architect

Lebanon, NH · On-site

Guide the integration of AI/ML capabilities into analytics platforms , including predictive, prescriptive, and generative AI use cases. * Collaborate with Data Science, Engineering, Security, and ...

D-H Lebanon-MHMH

Senior Database Developer

Lebanon, NH · On-site

$90K - $144K/yr

Provides mentoring and assistance to analysts and develops a deep understanding of the data, its ... Bachelor's degree in Statistics, Health Informatics, Computer Science or related field is preferred.

Elyon International

Senior Management Analyst

Hanover, NH · Remote

$110K - $120K/yr

The position reviews object models, data models, and metadata repositories to structure information ... A Bachelor of Science degree in a relevant field of study. * Demonstrated understanding of ...

New

Repligen

Senior Scientist

Lebanon, NH

$115K - $145K/yr

... analysis, potency, stability assays) * Broad scientific understanding spanning separations, protein chemistry, and bioprocessing * Strong communication skills with the ability to translate data into ...

Repligen Corporation

Senior Scientist

Lebanon, NH · On-site

$115K - $145K/yr

... analysis, potency, stability assays) * Broad scientific understanding spanning separations, protein chemistry, and bioprocessing * Strong communication skills with the ability to translate data into ...

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All JobsData Analyst Data Science JobsData Analyst Data Science Jobs in White River Junction, VT

Data Analyst Data Science information

See White River Junction, VT salary details

$32.4K

$78.7K

$129.6K

How much do data analyst data science jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data analyst data science in White River Junction, VT is $78,745.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,600.00 and $92,400.00 per year, depending on experience, location, and employer.

What does a data analyst in data science do?

A Data Analyst in Data Science collects, processes, and analyzes large sets of data to help organizations make informed decisions. They use statistical techniques and data visualization tools to identify trends, patterns, and insights from data. Their responsibilities often include cleaning data, creating reports, and communicating findings to stakeholders. Data Analysts play a key role in helping businesses optimize operations, understand customer behavior, and solve complex problems using data-driven approaches.

What are the key skills and qualifications needed to thrive as a data analyst in data science?

To thrive as a Data Analyst in Data Science, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, along with industry-recognized certifications, is highly valued. Attention to detail, problem-solving abilities, and effective communication skills help you interpret data insights and convey findings to stakeholders. These skills are crucial for transforming raw data into actionable intelligence that drives strategic business decisions.

How do data analysts in data science typically collaborate with other departments or teams?

Data Analysts in Data Science frequently work cross-functionally, partnering with teams such as engineering, product management, marketing, and business intelligence. They translate complex data findings into actionable insights and tailor their communication to both technical and non-technical stakeholders. Regular collaboration may involve participating in meetings to understand business needs, designing dashboards for different teams, and providing data-driven recommendations to support company objectives. This collaborative environment not only enhances project outcomes but also fosters continuous learning and professional growth.

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

AspectData Analyst Data ScienceData Engineer
Required SkillsStatistics, programming (Python, R), data visualizationDatabase systems, ETL pipelines, programming (Python, Java)
Work EnvironmentAnalyzing data, building models, reportingBuilding and maintaining data infrastructure
CertificationsData Science certifications, SQL, PythonCloud certifications, database management
Industry UsageBusiness analysis, predictive modelingData infrastructure, big data systems

Data Analyst Data Science focuses on analyzing data and creating models to inform decisions, while Data Engineers build the systems that collect, store, and process data. Both roles require programming skills and often overlap in tools like Python and SQL, but their core responsibilities differ significantly.

What are popular job titles related to Data Analyst Data Science jobs in White River Junction, VT?

For Data Analyst Data Science jobs in White River Junction, VT, the most frequently searched job titles are:

What cities near White River Junction, VT are hiring for Data Analyst Data Science jobs?

Cities near White River Junction, VT with the most Data Analyst Data Science job openings:

Data Analyst Data Science jobs near you
Infographic showing various Data Analyst Data Science job openings in White River Junction, VT as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 11% Part Time, and 6% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $78,745 per year, or $37.9 per hour.

Manufacturing Data Analyst (On-Site)

Whelen Engineering

NH • On-site

Full-time

Posted 9 days ago

Whelen Engineering rating

6.4

Company rating: 6.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

136th of 159 rated electronics manufacturers

Job description

Manufacturing Data Analyst (On-Site)
Department: Office NH
Employment Type: Full Time
Location: Charlestown, NH
Description
We are seeking a Manufacturing Data Analyst with a strong operations background to help turn manufacturing, supply chain, quality, maintenance, inventory, and business process data into actionable insights. This role is ideal for someone who understands how operations work across functions and can translate operational questions into reliable data, clear dashboards, and practical recommendations that improve safety, quality, delivery, cost, productivity, and customer service.
Key Responsibilities
  • Analyze operations, manufacturing, supply chain, quality, maintenance, inventory, and customer service data to identify trends, bottlenecks, risks, and improvement opportunities.
  • Develop and maintain dashboards, reports, and scorecards that track key operational metrics such as throughput, yield, scrap, rework, downtime, labor utilization, cycle time, inventory accuracy, schedule attainment, supplier performance, on-time delivery, and customer service levels.
  • Partner with operations leaders, production teams, supply chain, planning, quality, engineering, maintenance, finance, and customer-facing teams to understand business needs and translate them into data-driven solutions.
  • Validate data accuracy, reconcile discrepancies, and document data sources, definitions, assumptions, and refresh processes.
  • Support continuous improvement initiatives by identifying root causes, quantifying opportunities, and measuring the impact of process changes across operational functions.
  • Use data to support capacity planning, labor planning, production scheduling, inventory optimization, supplier performance management, quality improvement, and operational performance reviews.
  • Create clear, concise presentations and recommendations for operations leadership and cross-functional stakeholders.
  • Help improve data collection processes, reporting standards, and analytics workflows across operations.

Skills, Knowledge and Expertise
  • Bachelor's degree in Operations Management, Supply Chain, Engineering, Business Analytics, Data Analytics, Statistics, Information Systems, or a related field; equivalent practical experience may be considered.
  • 3+ years of experience in data analysis, operations analysis, supply chain analytics, manufacturing analytics, quality analytics, industrial engineering, or a similar role.
  • Hands-on experience working in or closely with an operations environment such as manufacturing, supply chain, distribution, quality, planning, or customer operations.
  • Strong proficiency with Microsoft Excel and data visualization tools such as Power BI, Tableau, or similar platforms.
  • Experience using SQL or other querying tools to extract, transform, and analyze data from databases, ERP systems, MES platforms, quality systems, supply chain systems, or other operational systems.
  • Strong understanding of operational metrics, process flows, constraints, tradeoffs, and continuous improvement concepts.
  • Ability to communicate complex data findings in a clear, practical way for both technical and non-technical audiences.
  • Strong attention to detail, problem-solving ability, and comfort working with incomplete or imperfect operational data.

Preferred Qualifications
  • Advanced proficiency with Microsoft Excel, including formulas, pivot tables, data modeling, data validation, and analysis of large operational data sets.
  • Experience building, maintaining, and improving Tableau dashboards, reports, and visualizations for operations, supply chain, quality, or manufacturing teams.
  • Ability to translate operational questions into clear Tableau views, KPIs, filters, and scorecards that support decision-making at multiple levels of the organization.
  • Experience connecting, cleaning, and validating data from ERP, MRP, MES, CMMS, WMS, CRM, quality management systems, or other operational systems.
  • Familiarity with Lean, Six Sigma, value stream mapping, root cause analysis, standard work, or operational excellence practices.
  • Knowledge of operational performance measures such as OEE, downtime, yield, scrap, labor efficiency, capacity, inventory turns, forecast accuracy, supplier performance, cost drivers, and service levels.
  • Experience supporting multi-site operations or complex environments that include manufacturing, supply chain, quality, or distribution functions.
  • Experience evaluating additional analytics, automation, or reporting tools when supported by a clear business need and return on investment.

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