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Weekend Data Science Jobs in Idaho (NOW HIRING)

Kochava

Data Scientist

Sandpoint, ID · On-site

You will work across model development, experimental design, and data workflows - solving difficult data science problems with pragmatic, scalable solutions that make a real difference to the ...

Kochava

Data Scientist

Sandpoint, ID · On-site

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 ...

Micron Technology

Sr Data Scientist

Boise, ID · On-site

$100 - $125/hr

As a Data Science Engineer at Micron, you will employ techniques and theories drawn from mathematics, statistics, semiconductor physics, materials science, and information technology to uncover ...

Simplot Company

Data Scientist III

Boise, ID · On-site

$125 - $150/hr

Participate as a member of a data science team. May provide technical leadership for small project teams depending on experience and project needs. * Apply technical knowledge to interpret business ...

J.R. Simplot Company

Sr. Data Scientist

Boise, ID · On-site

Participate as a member of a data science team. May provide technical leadership for small project teams depending on experience and project needs. * Apply technical knowledge to interpret business ...

Simplot Company

Sr. Data Scientist

Boise, ID · On-site

Key ResponsibilitiesParticipate as a member of a data science team.May provide technical leadership for small project teams depending on experience and project needs.Apply technical knowledge to ...

Simplot

Sr. Data Scientist

Boise, ID · On-site

Participate as a member of a data science team. May provide technical leadership for small project teams depending on experience and project needs. * Apply technical knowledge to interpret business ...

Simplot

Sr. Data Scientist

Boise, ID · On-site

Participate as a member of a data science team. May provide technical leadership for small project teams depending on experience and project needs. * Apply technical knowledge to interpret business ...

Lam Research Salzburg GmbH

Data Scientist 3

Boise, ID · On-site

$125 - $150/hr

Maintain active engagement with customer's IT and Data Science/Analytics teams * Provide structured feedback to Lam EI Dev and Product teams on: * Feature gaps * Operational pain points * Scalability ...

Computech Corporation

Data Scientist

Boise, ID · On-site

Data Scientist Location: Boise, Idaho Duration: 3 years on a part time basis (25% utilization) Required Skil ls * Should have worked in healthcare industry either at a provider, payer or HIE * Expert ...

Lam Research

Data Scientist 3

Boise, ID · Hybrid

... Data Science/Analytics teams Provide structured feedback to Lam EI Dev and Product teams on: Feature gaps Operational pain points Scalability concerns Contribute to broader Lam EI strategy ...

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All JobsData Science JobsWeekend Data Science JobsWeekend Data Science Jobs in Idaho

Weekend Data Science information

What is a weekend data science?

A Weekend Data Science job typically refers to a part-time or contract-based data science position where the primary work hours are on weekends. These roles are ideal for students, professionals seeking extra income, or those looking to gain experience in the data science field without committing to a full-time weekday schedule. Weekend data scientists analyze data, build models, and generate insights just like full-time data scientists but with flexible or reduced hours that fit around a weekend schedule.

What skills and qualifications are needed to thrive as a weekend data scientist?

To thrive as a Weekend Data Scientist, you need strong analytical skills, proficiency in statistics, and expertise in programming languages such as Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau) is typically required. Excellent time management, problem-solving ability, and effective communication are crucial soft skills for delivering insights on tight weekend deadlines. These skills ensure that data-driven decisions can be made efficiently and accurately, even within limited time frames.

What challenges do data scientists working on weekends face, and how can they be managed?

Data scientists working weekend shifts often encounter challenges such as limited access to colleagues for collaboration or support, since many team members may not be available outside standard business hours. Additionally, urgent issues or data anomalies may require quick, independent problem-solving. Proactive communication with weekday teams, thorough documentation, and setting up clear protocols for handoffs can help manage these challenges and ensure smooth workflow continuity.

What is the difference between Weekend Data Science vs Part-Time Data Analyst?

AspectWeekend Data SciencePart-Time Data Analyst
CredentialsTypically requires a degree in data science, statistics, or related fieldOften requires a degree or relevant experience in data analysis or related fields
Work EnvironmentProject-based, flexible hours, often remote or on-site during weekendsFlexible hours, may be remote or on-site, often with less technical complexity
Industry UsageUsed in tech, finance, healthcare, and startups for specialized projectsCommon in retail, marketing, and small businesses for routine data tasks

Weekend Data Science roles focus on complex data projects requiring advanced skills, often during weekends, while Part-Time Data Analysts handle routine data tasks with less technical depth, offering flexible schedules. Both roles serve different needs but share a focus on data work outside standard hours.

Do weekend data scientists work on weekends?

Weekend data scientists may work on weekends depending on project deadlines, company policies, or client needs. Typically, data science roles involve regular weekday hours, but some positions require weekend work, especially in roles with flexible or project-based schedules. It is important to clarify work hours during the hiring process or in job descriptions.

What are the most commonly searched types of Data Science jobs in Idaho?

The most popular types of Data Science jobs in Idaho are:

What are popular job titles related to Weekend Data Science jobs in Idaho?

For Weekend Data Science jobs in Idaho, the most frequently searched job titles are:

What job categories do people searching Weekend Data Science jobs in Idaho look for?

The top searched job categories for Weekend Data Science jobs in Idaho are:

Weekend Data Science jobs near you

Data Scientist

Kochava

Sandpoint, ID • On-site

Full-time

Re-posted 9 hours ago

Job description

Kochava provides a unified platform with solutions for advertisers and publishers across the omni-channel advertising ecosystem to link media investments to outcomes.  
 
Kochava is an industry leader in the advertising ecosystem, providing tools and technologies for leading brands, agencies, and premium publishers for measurement and attribution, media mix modeling (MMM), and search ads optimization.
 
We enable the visibility into and management of trillions of data points, hundreds of millions of users, and billions of dollars in lifetime value (LTV) and paid ad spend. Our suite of solutions are used as a growth stack for leading brands and publishers - empowering them to see and manage their data and unleash the power of their connected audiences.

We are looking for a talented and driven Data Scientist to join our team. In this role, you will be a significant and autonomous contributor, delivering end-to-end machine learning solutions and major analytical initiatives that directly drive business value. You will work across model development, experimental design, and data workflows - solving difficult data science problems with pragmatic, scalable solutions that make a real difference to the business.
 
Role Location: Sandpoint, Idaho
Job 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.
Experience/Skills 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.
Bonus
  • 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.
Kochava began in 2011 when a team of mobile and gaming professionals saw the need to better understand the feedback loop of user acquisition, engagement, and LTV for mobile applications. Through the process of creating apps for customers from a wide range of industries, we were repeatedly asked if we could shed some light on what media advertising efforts were converting and the effectiveness of their mobile ad spend by partner. Realizing a solution to these questions wasn't readily available, we started designing and building a mobile measurement platform that would become Kochava.   
 
 
Kochava is an equal opportunity employer committed to building a team culture that celebrates diversity and inclusion.
 
 
Please be advised that Kochava will never ask candidates to pay any fees or provide sensitive financial information at any point during the recruitment or onboarding process. We do not charge fees for applications, interviews, training, equipment, or background checks. 
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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