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Remote Manufacturing Data Scientist Jobs in Utah

Audiohook

Data Scientist

Eden, UT · On-site +1

Communicate clearly and proactively in a remote-first environment Qualifications Required * Bachelor\'s or Master\'s degree in Statistics, Economics, Data Science, Computer Science, or related ...

Hexcel Corporation

R&D Data Scientist

Salt Lake City, UT · On-site +1

We invite you to join the Hexcel team at various manufacturing sites, sales offices and R&D centers ... Master's degree in data science, Materials Science, Chemical Engineering, Mechanical Engineering ...

Bread Financial

Lead Data Scientist

Draper, UT · On-site +1

$144K - $250K/yr

The Lead Data Scientist is pivotal in generating insights and supporting the enterprise's data ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Alphia

R&D Scientist

Ogden, UT · On-site +1

Alphia, one of the nation's leading custom pet food manufacturing companies, is looking for a ... Collect and interpret data and make recommendations. * Experience with working effectively in a ...

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Remote Manufacturing Data Scientist information

How does a remote manufacturing data scientist typically collaborate with onsite engineering and production teams?

As a Remote Manufacturing Data Scientist, collaboration with onsite teams is often facilitated through regular virtual meetings, shared dashboards, and collaborative project management tools. You may analyze production data, develop predictive models, and then present insights and recommendations to engineers and plant managers via video calls or detailed reports. Building strong communication skills and familiarity with digital collaboration platforms is essential for bridging the gap between remote analytics and hands-on manufacturing processes. Proactively seeking feedback and clarifying technical requirements with onsite teams ensures your data-driven solutions are both practical and impactful.

What does a remote manufacturing data scientist do?

A Remote Manufacturing Data Scientist analyzes large sets of manufacturing data to uncover insights, optimize processes, and support decision-making, all while working offsite. They use statistical methods, machine learning, and data visualization tools to identify patterns, predict equipment failures, and recommend improvements for efficiency and quality. Collaborating with engineering and production teams, they help implement data-driven solutions without being physically present at the manufacturing facility. Their work contributes to reducing costs, improving productivity, and ensuring product quality in the manufacturing sector.

What are the key skills and qualifications needed to thrive as a remote manufacturing data scientist?

To thrive as a Remote Manufacturing Data Scientist, you need expertise in data analytics, statistical modeling, and a solid educational background in fields like computer science, engineering, or statistics. Familiarity with programming languages (such as Python or R), machine learning platforms, and manufacturing-specific systems like ERP or MES is typically required. Strong problem-solving skills, attention to detail, and effective remote communication are essential soft skills for collaborating with cross-functional teams. These competencies enable you to extract actionable insights from complex manufacturing data, driving process improvements and operational efficiency from a remote setting.

What is the difference between Remote Manufacturing Data Scientist vs Remote Manufacturing Engineer?

AspectRemote Manufacturing Data ScientistRemote Manufacturing Engineer
Required CredentialsDegree in Data Science, Statistics, or related field; proficiency in data analysis toolsDegree in Mechanical, Industrial, or Manufacturing Engineering; technical skills in manufacturing processes
Work EnvironmentPrimarily analytical, working with data sets and software tools remotelyFocus on process design, optimization, and technical implementation, often involving remote collaboration
Industry UsageUsed across manufacturing sectors for data-driven decision makingApplied in designing and improving manufacturing systems and processes

The main difference is that a Remote Manufacturing Data Scientist focuses on analyzing manufacturing data to inform decisions, while a Remote Manufacturing Engineer concentrates on designing and optimizing manufacturing processes. Both roles may work remotely and require technical expertise, but their core responsibilities differ significantly.

What are the most commonly searched types of Manufacturing Data Scientist jobs in Utah? The most popular types of Manufacturing Data Scientist jobs in Utah are:
What are popular job titles related to Remote Manufacturing Data Scientist jobs in Utah? For Remote Manufacturing Data Scientist jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Remote Manufacturing Data Scientist jobs in Utah look for? The top searched job categories for Remote Manufacturing Data Scientist jobs in Utah are:
What cities in Utah are hiring for Remote Manufacturing Data Scientist jobs? Cities in Utah with the most Remote Manufacturing Data Scientist job openings:
Remote Manufacturing Data Scientist jobs near you

Data Scientist

Audiohook

Eden, UT • On-site, Remote

Full-time

Medical, Dental, Vision, PTO

Re-posted 10 days ago

Job description

Role Overview

The Data Scientist will own the measurement science behind Audiohook\'s performance audio advertising platform. You\'ll design and run incrementality tests, build and maintain marketing mix models, and apply causal analysis to quantify how Audiohook drives outcomes for advertisers. This role combines hands-on modeling with the opportunity to shape how we prove value to customers, sharpen our bidding and optimization systems, and influence product direction. You\'ll collaborate closely with Engineering, Product, Sales, and Customer Success to ensure measurement isn\'t just statistically sound but operationally useful.

Key ResponsibilitiesMarketing Measurement & Causal Inference

  • Design and run incrementality experiments (geo, ghost bidding, holdout, PSA) that quantify Audiohook\'s lift for advertisers

  • Build, maintain, and evolve marketing mix models (MMM) and multi-touch attribution analyses across customer campaigns

  • Apply causal inference methods — difference-in-differences, synthetic controls, instrumental variables, propensity scoring — to questions that can\'t be answered with RCTs

  • Translate measurement results into clear narratives for advertisers, internal stakeholders, and the product team

Modeling & Analysis

  • Partner with Engineering on the data and modeling layer that powers bidding, pacing, and optimization decisions

  • Develop and validate predictive models that improve campaign performance and platform efficiency

  • Instrument experiments and analyses for reproducibility, monitoring, and ongoing measurement quality

Cross-Functional Collaboration

  • Partner with Sales and Customer Success on measurement studies for priority accounts and renewals

  • Partner with Product on roadmap inputs grounded in causal evidence, not just descriptive data

  • Present findings to advertisers, internal teams, and leadership in clear, decision-ready formats

  • Communicate clearly and proactively in a remote-first environment

QualificationsRequired

  • Bachelor\'s or Master\'s degree in Statistics, Economics, Data Science, Computer Science, or related quantitative field

  • 3–5 years of applied data science experience with a focus on marketing measurement — incrementality, MMM, attribution, or causal analysis

  • Hands-on experience designing and analyzing experiments (A/B, geo, holdout) in a marketing or advertising context

  • Strong fluency in Python (pandas, statsmodels, scikit-learn, PyMC, or similar) and SQL

  • Solid grounding in statistical inference, regression, and causal methods

  • Ability to communicate technical results to non-technical audiences — advertisers, sales, leadership

  • Excellent attention to detail and intellectual honesty about model limitations

Preferred

  • Experience in adtech, digital advertising, or media measurement

  • Experience with Bayesian methods or Bayesian MMM frameworks (e.g., PyMC-Marketing, LightweightMMM, Robyn)

  • Experience working with large-scale ad event data (impressions, clicks, conversions) and modern data stacks (e.g., Iceberg, Snowflake, BigQuery)

  • Experience in a startup or high-growth company

  • Comfort using AI tools to accelerate exploratory analysis, code, and write-ups while maintaining methodological rigor

What We Offer

  • Fully remote work environment

  • Competitive salary and equity opportunities

  • Performance bonuses

  • Health, dental, and vision benefits

  • Other benefits such as daily lunch stipend, monthly wifi, cell phone and subscription reimbursement, and annual hardware stipend

  • Flexible PTO and remote-friendly culture

  • Bi-annual Corporate Offsites

  • Opportunity to help shape a function at a rapidly scaling tech company

Apply