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Data Science Engineer Jobs in Oregon (NOW HIRING)

$114K/yr

The Data Scientist 2 creates complex machine learning models used to identify key data features ... Master's degree in a quantitative field like computer science, engineering, statistics, mathematics ...

Entry Level Data Engineer

Portland, OR · On-site

$121K - $145K/yr

Data analysts/data scientists * Machine learning engineers Who Should Apply * Recent graduates in Computer Science, Engineering, Mathematics, or Statistics who want a career in IT. * Candidates of ...

Entry Level Data Engineer

Beaverton, OR · On-site

$120K - $145K/yr

Data analysts/data scientists * Machine learning engineers Who Should Apply * Recent graduates in Computer Science, Engineering, Mathematics, or Statistics who want a career in IT. * Candidates of ...

OR · On-site

Partner with Engineering and Data Science to define requirements for secure, scalable, compliant RWD infrastructure and analytic environments. * Ensure data quality, interoperability, and governance ...

OR

$85K/yr

As Manager I, Data Science, you will work with a team of analysts, data scientists, and engineers ... You will use a combination of statistics, programming, and domain knowledge to solve problems and ...

... our data science function. You'll lead end-to-end growth initiatives-from acquisition and ... Reporting to the VP of Engineering, you'll operate as a true division leader-building systems ...

OR · On-site

Ensure GxP compliance in data science programming for clinical trials. * Manage budgets, vendor relationships, and third-party deliverables to maintain quality and efficiency. Executive Communication:

Translate business and operational needs into scalable data science solutions and modeling approaches * Perform feature engineering, data preparation, and exploratory analysis to support model ...

OR · On-site

Experience with prompt engineering for LLMs * You bring solid data science fundamentals and don't stop at exploratory analysis . You're interested in testing hypotheses, evaluating tradeoffs, and ...

Collaborate closely with engineering, analytics, AI, and product teams to align data science models and insights with broader business goals * Communicate findings and model results clearly to non ...

Our team of analysts, scientists, engineers, and strategists hail from diverse backgrounds yet share a passion for using data to solve the world's greatest social and analytical challenges. Since our ...

You'll contribute to data science systems across multiple SaaS products with end-to-end influence ... Collaborate across Product, Data, and Engineering teams to deliver data-driven solutions * Support ...

You'll contribute to data science systems across multiple SaaS products with end-to-end influence ... Collaborate across Product, Data, and Engineering teams to deliver data-driven solutions * Support ...

D in Data Science, Statistics, Applied Mathematics, Engineering, or similar quantitative discipline. * Core Technical Stack: Strong proficiency in SQL and Python, with deep expertise in the data ...

Senior Data Scientist

OR · On-site +1

$140K - $190K/yr

Excellent teamwork and meticulous verbal/written communication abilities, with a track record of partnering with engineering and product teams to translate data science work into actionable business ...

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Showing results 1-20

Data Science Engineer information

See Oregon salary details

$47K

$137.1K

$187.7K

How much do data science engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for data science engineer in Oregon is $137,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,100.00 and $145,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What are popular job titles related to Data Science Engineer jobs in Oregon? For Data Science Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Data Science Engineer jobs in Oregon look for? The top searched job categories for Data Science Engineer jobs in Oregon are:
What cities in Oregon are hiring for Data Science Engineer jobs? Cities in Oregon with the most Data Science Engineer job openings:
Data Science Manager, Gen AI - SFL Scientific

Data Science Manager, Gen AI - SFL Scientific

Deloitte

Portland, OR • On-site

Other

Posted 19 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

  • Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
  • Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
  • Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
  • Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
  • Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
  • Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
  • Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
  • Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
  • Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
  • 4+ years of experience managing teams and delivering complex and critical projects
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
  • Experience with developing and testing GenAI solutions
  • Experience in a client-facing role or internal AI product development role
  • Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

  • Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
  • Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
  • Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
  • Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
  • Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
  • Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
  • Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
  • Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
  • Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNN...

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