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Computational Data Analytics Jobs in Utah (NOW HIRING)

Degree in computational biology, bioinformatics, computer science or similar. * Experience analyzing complex multi-omic datasets, including human or single cell data. * Experience implementing, and ...

Join us on this journey as we execute this mission-critical contract providing high-end analytics ... a substantial computational component may be considered if it includes a concentration of ...

Postdoctoral Fellow I

Logan, UT · On-site

$42K - $57K/yr

Ph.D. degree in Computational Biology, Genomics, Bioinformatics, Computer Science or highly related field. * Experience in developing Machine Learning-based models and large-scale data analysis ...

Postdoctoral Fellow I

Logan, UT · On-site

$42K - $57K/yr

Ph.D. degree in Computational Biology, Genomics, Bioinformatics, Computer Science or highly related field. * Experience in developing Machine Learning-based models and large-scale data analysis ...

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Computational Data Analytics information

See Utah salary details

$22

$49

$86

How much do computational data analytics jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for computational data analytics in Utah is $49.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.05 and $56.44 per hour, depending on experience, location, and employer.

What is computational data analysis?

Computational data analysis is a process used in data analytics roles to examine large datasets using algorithms, statistical models, and programming tools like Python or R. It involves cleaning, processing, and interpreting data to extract meaningful insights and support decision-making.

Which is better, DS or CS?

For a Computational Data Analytics role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes algorithms, programming, and software development. The choice depends on the specific job requirements and your career goals, but proficiency in programming languages like Python or R and understanding of data management are essential in both fields.

How does a Computational Data Analyst typically collaborate with cross-functional teams to deliver data-driven insights?

Computational Data Analysts frequently work alongside professionals from various departments, such as engineering, product management, and business strategy. They gather requirements, clarify analysis goals, and present findings in clear, actionable terms. Regular meetings and collaborative tools are often used to ensure alignment, while analysts translate complex data patterns into practical recommendations that support decision-making across the organization. This teamwork not only enhances the impact of their analyses but also provides valuable opportunities for learning and professional growth.

What are the key skills and qualifications needed to thrive as a Computational Data Analytics professional, and why are they important?

To thrive as a Computational Data Analytics professional, you need strong quantitative skills, proficiency in statistics, and expertise in data manipulation, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with data visualization tools (e.g., Tableau, Power BI), and knowledge of machine learning frameworks are commonly required. Excellent problem-solving abilities, effective communication, and the capacity to work collaboratively make candidates stand out. These skills enable professionals to extract actionable insights from complex datasets, drive informed decision-making, and add significant value to organizations.

Is 40 too late for data science?

Computational Data Analytics professionals can enter the field at any age, as success depends on skills, experience, and continuous learning. Many data scientists start or transition into the field later in life by acquiring relevant certifications, programming skills, and domain knowledge, making age less of a barrier than skill development and adaptability.

What is the difference between Computational Data Analytics vs Data Scientist?

AspectComputational Data AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's or Master's in Data Science, Computer Science, Statistics, or related fields
Work EnvironmentData analysis teams, research labs, tech companiesData analysis teams, research labs, tech companies
Employer & Industry UsageTech, finance, healthcare, academiaTech, finance, healthcare, academia
Common Search & ComparisonYesYes

Computational Data Analytics focuses on developing algorithms and computational methods to analyze large datasets, often emphasizing programming and algorithm design. Data Scientists combine statistical analysis, machine learning, and domain expertise to interpret data and generate insights. While both roles require similar educational backgrounds and work environments, Computational Data Analytics leans more toward algorithm development, whereas Data Scientists focus on modeling and interpretation.

What is computational data analytics?

Computational data analytics is the process of using computational methods, algorithms, and systems to analyze large and complex datasets. This field combines principles from computer science, mathematics, and statistics to extract meaningful insights and patterns from data. Professionals in computational data analytics use tools such as machine learning, data mining, and statistical modeling to solve real-world problems in various industries. Their work often involves programming, data visualization, and working with big data platforms.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Science Director, Chief Data Officer, or Analytics Executive typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in machine learning, statistical analysis, and leadership, along with extensive experience and often advanced degrees or certifications.
What are popular job titles related to Computational Data Analytics jobs in Utah? For Computational Data Analytics jobs in Utah, the most frequently searched job titles are:
Associate Director, Computational Biology - Early Discovery

Associate Director, Computational Biology - Early Discovery

Recursion

Salt Lake City, UT

$200K - $220K/yr

Other

Re-posted 17 days ago


Job description

The Impact You'll Make

As an Associate Director within Recursion's early discovery team, you will be at the forefront of reimagining drug discovery from first principles. You will lead a team of world-class computational biologists focused on identifying and advancing the next generation of oncology targets and therapeutics to fill our internal pipeline. You will act as a "player-coach," balancing direct technical contribution with the mentorship and strategic leadership of a high-performing team. Your mission is to integrate Recursion's massive datasets-phenomics, transcriptomics, genomics, proteomics-to nominate novel targets, validate disease biology, and define the precision oncology strategies to advance our most promising therapeutic targets into full-fledged drug discovery programs.

This is a highly collaborative role: you will partner with biologists, data scientists, platform and data engineers, and translational experts to develop and scale methods for target discovery in oncology and immunological diseases. The ideal candidate has strong stakeholder management, technical communication, and 3+ years biotech or pharma experience in early drug discovery. 

In this role, you will:

  • Drive Target Discovery: Evaluate the molecular evidence for target nomination and validation, leveraging Recursion's platform to identify novel vulnerabilities in disease biology
  • Lead and mentor a team of data scientists and computational biologists, fostering a culture of scientific rigor, bold experimentation, delivery, and continuous professional growth. 
  • Pilot novel methods for target discovery, disease biology validation, and early patient population hypotheses to send programs into nomination cascades
  • Define internal criteria for target data packages and early patient population strategy
  • Connect your team's innovative analysis methods to platform and engineering teams so that we solve the current project and accelerate future ones
  • Collaborate cross-functionally: Partner with biologists, medicinal chemists, translational, and clinical leads to build compelling data packages that drive program milestones and portfolio investment decisions. 
  • Present data analysis to external decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients.

The Team You'll Join 

Our group is a bold, agile, diverse collective of computational drug discovery scientists deeply focused on the singular goal of bringing new therapeutics into the clinic at an accelerated pace. Our expertise spans precision oncology, I&I (immunology and inflammation), and neuroscience and we focus on advancing novel, targeted therapies for these disease areas. We partner closely with other functions to design and execute impactful and decisional data analyses for new targets and drug programs and are responsible for data strategy across the portfolio. 

The Experience You'll Need

  • PhD in a relevant field (computational biology, bioinformatics, cancer biology, immuno-oncology, etc.) with a very strong computational focus and 3+ years of experience in biotech or pharma industry OR MS in a relevant field and 5+ years of experience in biotech or pharma industry solving fundamental problems in early drug discovery
  • Domain expertise in oncology or immunological diseases
  • Strong understanding of patient genetics and druggability of disease relevant pathways
  • Experience applying computational methods (including probabilistic, statistical, and/or machine learning techniques) to analyze and integrate complex biological and/or human clinical data in a high level programming language such as Python or R
  • Exceptional data visualization skills
  • A track record of managing and developing direct reports within a scientific or technical environment
  • Excellent cross-functional communication skills, including an ability to explain complex scientific concepts to a variety of audiences using a combination of plots, documents, and presentations

Nice To Have:

  • Experience building a target discovery engine in oncology or immunological diseases
  • Experience designing high-throughput screens with CRISPR or small molecule perturbations to validate therapeutic hypotheses
  • Previous exposure to translational and/or clinical development programs to guide selection of relevant models for target validation experiments

Working Location & Compensation:

This is an office-based, hybrid position at our US headquarters located in Salt Lake City, Utah. Employees are expected to work in the office at least 50% of the time.

At Recursion, we believe that every employee should be compensated fairly. Based on the skills, experience, and qualifications needed for this role, the estimated annual base salary range is: $200,000-$220,500. In addition to base salary, this role is eligible for an annual bonus, equity compensation, and a comprehensive benefits package.

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