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Data Science Phd Jobs in Oregon (NOW HIRING)

OR · On-site

PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field ... Experience building data science teams from scratch or through periods of rapid growth * Prior work ...

PhD in health informatics, statistics, data science, or computer science * Experience integrating EHR/HIE data via TEFCA, CommonWell, or comparable networks. * Health Economics & Outcomes Methods:

OR

$372K - $600K/yr

Advanced degree (PhD or Masters) in Computer Science, Statistics, Economics, Applied Mathematics, or related quantitative field 3+ years experience with statistics / inference, ideally in an ...

Overview This is a general posting for multiple Senior Data Science roles open across our 4-sided ... MS/PhD in Statistics, Economics, Applied Mathematics, or a related field. Currently Opened Roles ...

OR · On-site

$160K - $180K/yr

The Data Science team works with feature-rich, high-volume clinical datasets and collaborates cross ... Master's or PhD in Statistics, Biostatistics, Epidemiology, Health Economics, Computer Science, a ...

Data Scientist

OR · Remote

$130K - $150K/yr

Degree or equivalent years of experience in data science, statistics, computer science, or similar ... Master's degree or PhD in math and/or statistics centric field of study * Experience on a data team ...

OR

$480K - $750K/yr

The Title & Launch Management Data Science and Engineering team is at the forefront of driving ... Master's or PhD in Machine Learning, Computer Science, or a closely related field. 6+ years of ...

Data Scientist

OR · On-site +1

You might thrive in this role if you have * 5+ years of experience in data science, applied ML, or ... An MS or PhD in a quantitative field Why Join Terzo * Opportunity to build and own a foundational ...

OR

$372K - $600K/yr

An advanced degree (Masters or PhD) in Statistics, Mathematics, Computer Science, Economics, or a ... Strong data manipulation and quantitative programming skills in SQL and Python or R Experience ...

An advanced degree (MS or PhD) in a technical discipline. This doesn't have to be in data science or ML specifically -- strong backgrounds in CS, statistics, physics, math, engineering, and related ...

OR · On-site

... data-driven decision-making. A Bit About You Minimum Qualifications * Master's or PhD in a quantitative field such as Computer Science, Mathematics, Engineering, or a related discipline. * 6+ years ...

OR · On-site

This clinical leadership role shapes the data validation pipeline for our cell-free DNA (cfDNA ... Advanced degree in Life Sciences (PhD, MD, PharmD, MS, RN, or equivalent scientific or clinical ...

Overview Instacart's Marketing Data Science and Analytics team partners across Marketing, Strategic ... Preferred Qualifications * 8+ years of relevant experience; advanced degree (MS/PhD) in a ...

Participate in other data science teams collaborating with your peers to support their projects ... PhD or Graduate degree in a quantitative discipline such as Computer Science/Engineering ...

Review and interpret scientific literature to provide contextually accurate and current insights ... Analyze data and interpret results to inform AI training datasets with precision * Apply ...

Staff Software Engineer, Data Infrastructure

OR · Remote

$114K - $137K/yr

Overview Instacarts Data Infrastructure organization builds and operates the systems that power our ... Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or ...

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Data Science Phd information

What can you do with a doctorate in data science?

A doctorate in data science prepares individuals for advanced roles such as data scientist, research scientist, or machine learning engineer, often involving complex data analysis, modeling, and algorithm development. It enables expertise in programming languages like Python or R, statistical methods, and data management tools, opening opportunities in academia, industry, and research institutions.

What are the key skills and qualifications needed to thrive as a Data Science PhD, and why are they important?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

Is PhD worth it for data science?

A PhD in data science can enhance expertise in advanced analytics, research, and specialized skills, which may lead to higher-level roles and increased salary potential. However, it also requires significant time and financial investment, and many data science positions value practical experience and skills in programming, machine learning, and data manipulation over formal degrees.

What is the salary of a PhD in data scientist?

A Data Science PhD typically earns between $100,000 and $150,000 annually, depending on experience, industry, and location. Advanced degrees and expertise in machine learning, statistical analysis, and programming tools like Python or R can lead to higher compensation, especially in tech and research sectors.

What are some common challenges faced by Data Science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

Is 40 too late for data science?

Data science PhDs can pursue careers at any age, including at 40 or older. Success depends on skills, experience, and continuous learning in areas like programming, statistics, and machine learning, rather than age alone.

What is a Data Science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.
What are popular job titles related to Data Science Phd jobs in Oregon? For Data Science Phd jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Data Science Phd jobs? Cities in Oregon with the most Data Science Phd job openings:
Director, Data Science/ML

Director, Data Science/ML

CookUnity

OR • On-site

Other

Medical, Vision, Retirement, PTO

Re-posted yesterday


Job description

The role:

We're looking for a Director, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics-you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale.

You'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution.

Responsibilities:Strategic Vision & Product Partnership
  • Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes
  • Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities
  • Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems
  • Translate complex product challenges into clear data science problems with measurable success criteria
  • Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration
  • Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.
Team Leadership & Development
  • Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems
  • Foster a culture of innovation, experimentation, and continuous learning within the data science organization
  • Create career development pathways that attract and retain top data science talent
  • Collaborate with Analytics Engineering to ensure seamless model deployment and monitoring
Advanced Analytics & ML Capabilities
  • Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey
  • Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning
  • Develop causal inference methodologies to understand true incrementality of product changes.
  • Ensure models are observable, explainable where needed, and continuously improved post-launch
Product Measurement & Impact
  • Define product success metrics and measurement frameworks that align with business objectives
  • Build scalable dashboards and monitoring systems that provide real-time visibility into product performance
  • Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimization

Qualifications:
  • 10+ years of experience in data science, with at least 5 years in leadership roles managing data scientists or ML engineers
  • Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling
  • Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor
  • Strong product sense and business acumen-ability to identify high-impact opportunities and translate them into data science initiatives
  • Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical
  • Excellent communication skills-ability to explain complex technical concepts to non-technical stakeholders and influence product strategy
  • Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow)
  • Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)
Preferred requirements:
  • PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field
  • Experience with real-time ML systems and feature stores
  • Background in recommendation systems or two-tower/multi-modal embeddings
  • Familiarity with generative AI and LLM applications in product contexts
  • Experience building data science teams from scratch or through periods of rapid growth
  • Prior work in subscription businesses or retention-focused products
  • Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)
What Success Looks Like
  • 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership
  • 12 months: Scaled the product data science function with key hires; delivered measurable improvements in personalization and customer engagement metrics; implemented robust experimentation frameworks used across product teams

Learn More About CookUnity

We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles - The values and behaviors that guide how we operate, collaborate, and scale.

We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect!


Benefits

  Health Insurance coverage

 401k Plan

 We grow, you grow: Stock Options Plan granted on Day 1

 Eligible for a bi-annual performance bonus

 Unlimited PTO

 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

 Paid Family leave

 Compassionate Leave: 3-5 days each time the need arises

 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

Wellness perks: access to fitness subsidies to build a healthy lifestyle

AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.

 Personalized Spanish coach

 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!