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Associate Data Scientist Jobs in Moscow, ID (NOW HIRING)

Alturas Analytics, Inc.

Assistant Scientist

Moscow, ID · On-site

$22.60/hr

... an Associate Scientist . In this role, employees begin by learning and performing laboratory ... Performs QC review of data Additional Duties and Tasks: * Performs other duties as needed or ...

Alturas Analytics, Inc

Assistant Scientist

Moscow, ID · On-site

$22.60/hr

... an Associate Scientist . In this role, employees begin by learning and performing laboratory ... Performs QC review of data Additional Duties and Tasks: * Performs other duties as needed or ...

Danaher

R&D Internships

Moscow, ID · On-site

You'll work in a collaborative environment alongside experienced scientists and contribute to real ... Supporting immunoassay development teams with experimental setup, data collection, and ...

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All JobsAssociate Data Scientist JobsAssociate Data Scientist Jobs in Moscow, ID

Associate Data Scientist information

See Moscow, ID salary details

$49.9K

$59.1K

$112K

How much do associate data scientist jobs pay per year?

As of Aug 20, 2026, the average yearly pay for associate data scientist in Moscow, ID is $59,063.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,200.00 and $51,700.00 per year, depending on experience, location, and employer.

What does an associate data scientist do?

An Associate Data Scientist supports data-driven decision-making by collecting, cleaning, and analyzing large datasets. They use statistical methods and programming languages like Python or R to identify trends, build predictive models, and generate insights for business problems. Working under the guidance of more experienced data scientists, they also help visualize data and communicate findings to technical and non-technical stakeholders. This entry-level role often involves learning new tools and techniques while contributing to real-world projects.

What does an associate data scientist do?

The duties of an associate data scientist are to analyze statistical data analysis on large sets and identify trends by using advanced mathematical and computer science skills. Their responsibilities often include assisting in the production of statistical models, tools, and processes. They typically are in the process of pursuing a master’s degree and report to a senior data scientist. The qualifications you need are a bachelor’s degree in statistics, computer science, or a related field as well as experience working with machine-learning and data mining algorithms.

What are some typical projects an associate data scientist might work on, and how do they collaborate with other team members?

As an Associate Data Scientist, you can expect to contribute to a range of projects such as developing predictive models, analyzing large datasets to uncover business insights, and supporting the deployment of machine learning solutions. Collaboration is key; you'll often work closely with data engineers to prepare and process data, as well as with business analysts and product managers to align your findings with organizational goals. Regular meetings, code reviews, and knowledge-sharing sessions are common, providing opportunities to learn from senior data scientists and broaden your technical skills.

What are the key skills and qualifications needed to thrive as an associate data scientist, and why are they important?

To thrive as an Associate Data Scientist, you need strong analytical skills, a solid foundation in statistics, and proficiency in programming languages like Python or R, typically supported by a degree in a quantitative field. Experience with data visualization tools (e.g., Tableau), machine learning libraries (e.g., scikit-learn), and database systems (e.g., SQL) is often required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating data insights into actionable business solutions. These skills and qualities are essential for extracting valuable insights from complex data and driving data-informed decision-making within organizations.

What is the difference between Associate Data Scientist vs Data Analyst?

AspectAssociate Data ScientistData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; certifications like Microsoft Excel or Tableau are common
Work EnvironmentCollaborates with data science teams, develops models, and analyzes complex datasetsPrepares reports, visualizes data, and provides insights for decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms focusing on predictive modelingCommon across various industries for business reporting and operational analysis

The Associate Data Scientist typically focuses on building models and advanced analytics, requiring programming skills and statistical knowledge. Data Analysts mainly interpret data through reports and visualizations, often with less emphasis on coding. Both roles are essential in data-driven organizations but differ in technical depth and responsibilities.

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Associate Data Scientist jobs near you

Associate Data / Business Analyst - 1056

Lightcast

Moscow, ID • On-site

Full-time

Re-posted 21 days ago

Job description

The Associate Data / Business Analyst at Lightcast develops and maintains standardized taxonomies for labor market data to ensure consistency, quality, and accuracy across the organization. This role analyzes labor market data, creates standardized classifications, collaborates with cross-functional teams, and supports data governance initiatives that enhance labor market intelligence.
Major Responsibilities:
  • Develop and maintain taxonomies for labor market data, including job titles, skills, education requirements, and industry classifications.
  • Analyze labor market data to identify patterns and establish standardized terms and classifications.
  • Partner with cross-functional teams to ensure taxonomies align with business needs and are integrated into data models and databases.
  • Implement and maintain data governance processes to ensure data quality, consistency, and accuracy.
  • Support labor market data integration and migration projects while maintaining taxonomy integrity.
  • Organize and analyze large, unstructured datasets.
  • Monitor industry trends and best practices related to labor market taxonomies, ontologies, and data governance.

Education and Experience:
  • Bachelor's degree in Computer Science, Information Science, Library Science, or a related field.
  • 1+ years of experience in labor market data management, analytics, taxonomy development, or a related field.
  • Strong analytical and problem-solving skills with exceptional attention to detail.
  • Experience working with large, unstructured datasets.
  • Familiarity with data modeling and database design principles.
  • Experience with SQL, Elasticsearch, KQL, SPARQL, or similar data query languages is preferred.
  • Experience with Python or R and data visualization tools such as Tableau, Looker, or Kibana is a plus.
  • Knowledge of labor market taxonomies and ontologies (e.g., NAICS, CIP, ESCO, O*NET-SOC) is preferred.
  • Familiarity with NLP or machine learning concepts is a plus.
  • Excellent written and verbal communication skills and the ability to work independently and collaboratively.

Lightcast is a global leader in labor market insights with our headquarters located in Moscow, ID (US) and other offices in the United Kingdom, Europe, and India. We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities.
Lightcast is proud to be an equal opportunity workplace and does not discriminate on the basis of federally protected statuses. Lightcast has always been, and always will be, committed to diversity of thought and unique perspectives. We seek dynamic professionals from all backgrounds to join our teams, and we encourage our employees to bring their authentic, original, and best selves to work.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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