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Associate Data Scientist Jobs in Portland, OR (NOW HIRING)

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering. * 7+ years of ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering. * 3+ years of ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering. * 5+ years of ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Assisting with creating the UAT plan, developing test scripts, coordinating data setup, and ... Bachelor's degree (in life sciences or computer science preferred) * Interpersonal and ...

Showing results 21-40

Associate Data Scientist information

See Portland, OR salary details

$61K

$72.2K

$136.8K

How much do associate data scientist jobs pay per year?

As of Aug 10, 2026, the average yearly pay for associate data scientist in Portland, OR is $72,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,600.00 and $63,100.00 per year, depending on experience, location, and employer.

What is the difference between Associate Data Scientist vs Data Analyst?

AspectAssociate Data ScientistData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; certifications like Microsoft Excel or Tableau are common
Work EnvironmentCollaborates with data science teams, develops models, and analyzes complex datasetsPrepares reports, visualizes data, and provides insights for decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms focusing on predictive modelingCommon across various industries for business reporting and operational analysis

The Associate Data Scientist typically focuses on building models and advanced analytics, requiring programming skills and statistical knowledge. Data Analysts mainly interpret data through reports and visualizations, often with less emphasis on coding. Both roles are essential in data-driven organizations but differ in technical depth and responsibilities.

What are the key skills and qualifications needed to thrive as an associate data scientist, and why are they important?

To thrive as an Associate Data Scientist, you need strong analytical skills, a solid foundation in statistics, and proficiency in programming languages like Python or R, typically supported by a degree in a quantitative field. Experience with data visualization tools (e.g., Tableau), machine learning libraries (e.g., scikit-learn), and database systems (e.g., SQL) is often required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating data insights into actionable business solutions. These skills and qualities are essential for extracting valuable insights from complex data and driving data-informed decision-making within organizations.

What does an associate data scientist do?

An Associate Data Scientist supports data-driven decision-making by collecting, cleaning, and analyzing large datasets. They use statistical methods and programming languages like Python or R to identify trends, build predictive models, and generate insights for business problems. Working under the guidance of more experienced data scientists, they also help visualize data and communicate findings to technical and non-technical stakeholders. This entry-level role often involves learning new tools and techniques while contributing to real-world projects.

What are some typical projects an associate data scientist might work on, and how do they collaborate with other team members?

As an Associate Data Scientist, you can expect to contribute to a range of projects such as developing predictive models, analyzing large datasets to uncover business insights, and supporting the deployment of machine learning solutions. Collaboration is key; you'll often work closely with data engineers to prepare and process data, as well as with business analysts and product managers to align your findings with organizational goals. Regular meetings, code reviews, and knowledge-sharing sessions are common, providing opportunities to learn from senior data scientists and broaden your technical skills.

What does an associate data scientist do?

The duties of an associate data scientist are to analyze statistical data analysis on large sets and identify trends by using advanced mathematical and computer science skills. Their responsibilities often include assisting in the production of statistical models, tools, and processes. They typically are in the process of pursuing a master’s degree and report to a senior data scientist. The qualifications you need are a bachelor’s degree in statistics, computer science, or a related field as well as experience working with machine-learning and data mining algorithms.

What can I do with an associate data scientist?

An associate data scientist analyzes data to identify patterns, build models, and support decision-making using tools like Python, R, or SQL. This role often involves collaborating with teams, developing predictive models, and gaining experience to advance to more senior data science positions.
What are the most commonly searched types of Data Scientist jobs in Portland, OR? The most popular types of Data Scientist jobs in Portland, OR are:
What are popular job titles related to Associate Data Scientist jobs in Portland, OR? For Associate Data Scientist jobs in Portland, OR, the most frequently searched job titles are:
What cities near Portland, OR are hiring for Associate Data Scientist jobs? Cities near Portland, OR with the most Associate Data Scientist job openings:
Infographic showing various Associate Data Scientist job openings in Portland, OR as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $72,156 per year, or $34.7 per hour.

Lead Forward Deployed Engineer - AWS

Deloitte

Portland, OR

$108K - $143K/yr

Full-time

Re-posted 22 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

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 $189,200 to $372,900.

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:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

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 $189,200 to $372,900.

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.

Education:Bachelor's DegreeEmployment Type:

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