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Data Science Visualization Jobs in Sandpoint, ID

Required : • 3+ years of hands-on Data Science experience. A formal degree is not required if you ... data visualization tools and communicating analytical findings clearly to non-technical ...

Identify and resolve data quality issues and analytical gaps; drive improvements to data science ... Experience working with data visualization tools and communicating analytical findings clearly to ...

Identify and resolve data quality issues and analytical gaps; drive improvements to data science ... Experience working with data visualization tools and communicating analytical findings clearly to ...

Identify and resolve data quality issues and analytical gaps; drive improvements to data science ... Experience working with data visualization tools and communicating analytical findings clearly to ...

Strong data analysis & visualization skills * Strong strategic thinking skills * Strong project and ... Bachelor's degree in Business Analytics, Information Systems, Computer Science, or comparable ...

Strong data analysis & visualization skills * Strong strategic thinking skills * Strong project and ... Bachelor's degree in Business Analytics, Information Systems, Computer Science, or comparable ...

Strong data analysis & visualization skills * Strong strategic thinking skills * Strong project and ... Bachelor's degree in Business Analytics, Information Systems, Computer Science, or comparable ...

Data Science Visualization information

See Sandpoint, ID salary details

$51.1K

$103.6K

$152.8K

How much do data science visualization jobs pay per year?

As of Sep 2, 2026, the average yearly pay for data science visualization in Sandpoint, ID is $103,580.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,200.00 and $116,400.00 per year, depending on experience, location, and employer.

What is data science visualization?

Data Science Visualization refers to the practice of creating graphical representations of data and analytical results to make complex information more understandable and actionable. Data visualization helps data scientists communicate insights, identify patterns, and inform decision-making by presenting data in charts, graphs, maps, and interactive dashboards. It bridges the gap between technical analyses and non-technical stakeholders, enabling clearer communication and more effective storytelling with data.

How does a data science visualization specialist typically collaborate with data scientists and other stakeholders during a project?

Data Science Visualization specialists play a key role in bridging the gap between complex data analysis and actionable insights. They often work closely with data scientists to understand the underlying data models and results, and then collaborate with business stakeholders to ensure visualizations are tailored to the audience's needs. Regular meetings, feedback sessions, and iterative design processes are common, enabling effective communication and ensuring that visual outputs are both accurate and impactful. This collaborative environment helps ensure that data-driven insights are easily understood and used for decision-making across the organization.

What are the key skills and qualifications needed to thrive as a data science visualization specialist, and why are they important?

To thrive in Data Science Visualization, you need a strong grasp of data analysis, statistics, and data storytelling, often supported by a degree in computer science, statistics, or a related field. Proficiency with visualization tools like Tableau, Power BI, or D3.js as well as programming languages such as Python or R is typically required. Creativity, attention to detail, and effective communication are valuable soft skills for translating complex data into clear, actionable visuals. These skills are crucial for transforming raw data into insights that drive informed business decisions.

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

AspectData Science VisualizationData Analyst
Required SkillsData visualization tools, programming (Python, R), statistical knowledgeExcel, SQL, basic statistics, data reporting
Work EnvironmentData science teams, research projects, advanced analyticsBusiness units, reporting, data cleaning
Industry UsageTech, finance, healthcare, researchRetail, marketing, finance, operations

Data Science Visualization focuses on creating advanced visual representations of complex data sets using programming and statistical tools, often within data science teams. Data Analysts primarily generate reports and dashboards using tools like Excel and SQL for business decision-making. While both roles involve data visualization, Data Science Visualization emphasizes technical, programming-based visualizations for in-depth analysis, whereas Data Analysts focus on accessible reports for business insights.

Infographic showing various Data Science Visualization job openings in Sandpoint, ID as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $103,580 per year, or $49.8 per hour.

Data Scientist

Kochava

Sandpoint, ID • On-site

Full-time

Re-posted 24 days ago


Job description

Job Summary:
Kochava is an industry leader in the advertising ecosystem, providing tools and technologies for measurement and attribution. They are seeking a talented and driven Data Scientist to deliver end-to-end machine learning solutions and analytical initiatives that drive business value.
Responsibilities:
• Design, build, and deploy production-grade machine learning models and analytical solutions that are robust, scalable, and maintainable by other data scientists.
• Apply a broad range of statistical methods and ML algorithms, using sound judgment on when — and when not — to use them.
• Write highly performant, well-documented, and reproducible code in Python and SQL.
• Collaborate with product managers, business stakeholders, and engineering teams to clarify requirements, scope analytical work, and deliver on project milestones.
• Make thoughtful trade-offs between model performance and interpretability, complexity and simplicity, and computational cost and accuracy.
• Identify and resolve data quality issues and analytical gaps; drive improvements to data science workflows and model reliability.
• Actively contribute to model reviews, experimental design discussions, team planning, and post-deployment performance evaluations.
• Work to find and address root causes of model performance issues, leaving systems better than you found them.
• Contribute to on-call support and take ownership of issues, driving resolutions or ensuring clear handoffs.
• Automate manual reporting tasks and contribute to operational excellence across the team.
• Mentor junior data scientists and actively participate in the hiring and interview process.
Qualifications:
Required:
• 3+ years of hands-on Data Science experience. A formal degree is not required if you have equivalent knowledge gained from experience.
• Strong proficiency in Python for statistical programming and machine learning development.
• Expertise writing high-performance SQL queries and working with large-scale datasets.
• Solid understanding of a broad range of statistical methods and machine learning algorithms.
• Demonstrated ability to independently deliver end-to-end model development — from problem definition through production deployment.
• Ability to build solutions that are pragmatic, consider business constraints, and can be maintained and extended by others.
• Experience working with data visualization tools and communicating analytical findings clearly to non-technical stakeholders.
• Strong sense of ownership — you document your work thoroughly, validate it rigorously, and ensure quality at every step.
• Collaborative mindset with the ability to work across teams, balance competing requirements, and influence peers constructively.
Preferred:
• Experience with MLOps practices, model monitoring, or automated reporting pipelines.
• Familiarity with experimental design and A/B testing frameworks.
• Track record of improving team workflows, data documentation practices, or analytical infrastructure.
• Experience mentoring junior data scientists or contributing to onboarding and training programs.
• Experience classifying, storing, and handling data in accordance with data governance policies.
• Experience with distributed computing and big data technologies such as Apache Spark.
• Experience with data visualization tools such as Tableau.
• Experience working with cloud data warehouses such as Amazon Redshift or Google BigQuery.
• Experience working with high volume and high velocity data in a distributed environment.
Company:
Kochava is a provider of secure, real-time data solutions for mobile and connected devices. Founded in 2011, the company is headquartered in Sandpoint, USA, with a team of 51-200 employees. The company is currently Growth Stage.