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Phd Data Scientist Jobs in Raleigh, NC (NOW HIRING)

Jobtailor

Data Scientist

Raleigh, NC · On-site

$110 - $170/hr

... Data Science, or a related quantitative field. * 3+ years of experience (with Bachelor's), 2+ years ... PhD) in applied statistical modeling and machine learning, with a track record of deployed ...

New

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site

Required : • Masters plus 7-10 years of work-related experience OR PhD with 6+ years of work ... lead and mentor junior data scientists, and collaborate with cross-functional teams. • ...

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site

Required : • Masters plus 7-10 years of work-related experience OR PhD with 6+ years of work ... lead and mentor junior data scientists, and collaborate with cross-functional teams. • ...

LexisNexis Risk Solutions

Lead Data Scientist

Raleigh, NC · On-site

$104.90 - $174.70/hr

## Lead Data ScientistApplylocations: Raleigh, NCtime type: Full timeposted on: Posted Yesterdayjob ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field* Experience ...

New

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site +1

$115K - $192K/yr

Do you want to help us build further data science capabilities? And are you eager to work on the ... Masters plus 7-10 years of work-related experience OR PhD with 6+ years of work-related experience.

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site +1

$115K - $192K/yr

Do you want to help us build further data science capabilities? And are you eager to work on the ... Masters plus 7-10 years of work-related experience OR PhD with 6+ years of work-related experience.

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site

$115K - $192K/yr

Do you want to help us build further data science capabilities? And are you eager to work on the ... Masters plus 7-10 years of work-related experience OR PhD with 6+ years of work-related experience.

LexisNexis

Lead Data Scientist

Raleigh, NC · On-site

$104K - $174K/yr

We are seeking a Lead Data Scientist toleads a team of junior members to support their development ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field

RELX

Lead Data Scientist

Raleigh, NC · On-site

$104K - $174K/yr

We are seeking a Lead Data Scientist to leads a team of junior members to support their development ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field

LexisNexis

Lead Data Scientist

Raleigh, NC

$104K - $174K/yr

We are seeking a Lead Data Scientist to leads a team of junior members to support their development ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field

TEKsystems

Principal Data Scientist

Raleigh, NC

$75 - $90/hr

Master's or PhD Preferred - 6-12+ years in Data Science / ML Engineering, with deep experience in LLM‑based systems. Proven experience building multi-agent architectures (planner‑executor ...

RELX Group plc

Lead Data Scientist

Raleigh, NC · On-site

$104K - $174K/yr

We are seeking a Lead Data Scientist toleads a team of junior members to support their development ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field

LexisNexis

Lead Data Scientist

Raleigh, NC

$104K - $174K/yr

We are seeking a Lead Data Scientist to leads a team of junior members to support their development ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field

慨正橡扯

Lead Data Scientist

Raleigh, NC · On-site

$104K - $174K/yr

We are seeking a Lead Data Scientist toleads a team of junior members to support their development ... PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field

New

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All JobsPhd Data Scientist JobsPhd Data Scientist Jobs in Raleigh, NC

Phd Data Scientist information

See Raleigh, NC salary details

$44.7K

$160.4K

$236.7K

How much do phd data scientist jobs pay per year?

As of Aug 7, 2026, the average yearly pay for phd data scientist in Raleigh, NC is $160,411.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,800.00 and $165,300.00 per year, depending on experience, location, and employer.

What is a PhD data scientist?

PhD Data Scientists are professionals who have earned a doctoral degree (PhD) in a relevant field, such as computer science, statistics, mathematics, or engineering, and work in roles focused on analyzing and interpreting complex data. They leverage advanced research skills, deep theoretical knowledge, and expertise in data modeling to solve challenging problems, build predictive models, and derive actionable insights for organizations. PhD Data Scientists often contribute to cutting-edge projects, publish research, and help bridge the gap between academic research and practical, real-world applications.

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

AspectPhd Data ScientistData Analyst
Required CredentialsPhD or Master's in Data Science, Statistics, or related fieldBachelor's or Master's in related field, often with certifications
Work EnvironmentResearch-focused, complex modeling, advanced analyticsBusiness reporting, data visualization, basic analysis
Employer & Industry UsageTech, academia, research institutions, large corporationsBusiness, marketing, finance, healthcare

Phd Data Scientists typically have advanced degrees and focus on complex modeling and research, while Data Analysts handle more straightforward data reporting and visualization tasks. Both roles are essential in data-driven organizations but differ in scope and expertise.

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

To thrive as a PhD Data Scientist, you need advanced expertise in statistics, machine learning, and data analysis, typically backed by a PhD in a quantitative field. Proficiency with programming languages like Python or R, experience with big data tools (e.g., Hadoop, Spark), and familiarity with cloud platforms and version control systems are commonly required. Strong problem-solving skills, communication abilities, and the capacity to explain complex concepts to non-technical stakeholders are crucial soft skills. These skills and qualities are essential for extracting actionable insights from complex datasets and driving data-informed decision-making in organizations.

What are some common challenges PhD data scientists face when transitioning from academia to industry roles?

PhD Data Scientists often encounter challenges when moving from academia to industry, such as adapting to faster project timelines, prioritizing business impact over exploratory research, and communicating complex findings to non-technical stakeholders. In industry, there is a greater emphasis on collaborative teamwork and delivering actionable insights that align with organizational goals. Building skills in agile development, stakeholder engagement, and product-focused thinking can help smooth the transition and ensure success in a corporate environment.
What are popular job titles related to Phd Data Scientist jobs in Raleigh, NC? For Phd Data Scientist jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Phd Data Scientist jobs in Raleigh, NC look for? The top searched job categories for Phd Data Scientist jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Phd Data Scientist jobs? Cities near Raleigh, NC with the most Phd Data Scientist job openings:
Phd Data Scientist jobs near you
Infographic showing various Phd Data Scientist job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, and 6% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $160,411 per year, or $77.1 per hour.

Data Scientist

Jobtailor

Raleigh, NC • On-site

$110 - $170/hr

Other

Posted 2 days ago

New

Job description

  • Design and implement statistical and machine learning models for time-series forecasting, anomaly detection, and asset health scoring across utility networks.
  • Build and maintain end-to-end ML pipelines on Databricks from feature engineering and model training to validation, deployment, and monitoring in production.
  • Apply classical statistical methods (GLMs, GAMs, mixed-effects models, Bayesian inference) alongside modern ML techniques (ensemble approaches, network analysis, neural networks) to solve grid operations problems.
  • Develop predictive maintenance and degradation models for utility infrastructure using telemetry and SCADA data at scale.
  • Translate ambiguous business problems into well-defined modeling problems with appropriate statistical frameworks - e.g., knowing when a LM/GLM is sufficient and when gradient boosting or deep learning is warranted.
  • Implement model monitoring, drift detection, and automated retraining workflows to maintain model performance over time.
  • Contribute to load forecasting, demand response optimization, and outage prediction systems.
  • Ensure model interpretability and explainability for utility stakeholders and regulatory compliance.
  • Contribute to internal knowledge-sharing on statistical best practices.
Requirements
  • Bachelor’s degree or equivalent in Statistics, Applied Mathematics, Physics, Engineering, Data Science, or a related quantitative field.
  • 3+ years of experience (with Bachelor’s), 2+ years of experience (with Masters), or 1+ years (with PhD) in applied statistical modeling and machine learning, with a track record of deployed production models.
  • Strong programming skills in Python (PySpark, pandas, NumPy, scikit-learn, statsmodels, XGBoost), R (tidyverse, lme4, glmmTMB, glmnet, mgcv), and SQL for large-scale data analysis.
  • Experience with time-series modeling (ARIMA, state-space models, LSTM, Darts, or similar) on high-volume meter data.
  • Exposure to Databricks ML ecosystem (Feature Store, Experiment Track, Model Serving, Mosaic AI) and MLflow.
  • Familiarity with distributed computing concepts - PySpark, Optuna/Ray, Spark SQL, partitioning strategies, and medallion architecture.
  • Understanding of software engineering principles - version control (Git), testing, CI/CD for ML systems.
  • Ability to communicate complex statistical/ML concepts to non-technical stakeholders.
Core Competencies

Demonstrates expertise in statistical modeling and machine learning for time-series forecasting and anomaly detection, with a strong focus on building and maintaining ML pipelines and ensuring model performance and interpretability. Proficient in translating business problems into statistical frameworks and communicating complex concepts to stakeholders.

Highest-signal resume keywords
  • Statistical Modeling
  • Machine Learning
  • Python Programming
  • Time-Series Modeling
  • Databricks ML Ecosystem
ATS Optimization KeywordsHard Skills
  • Statistical Methods
  • Machine Learning Techniques
  • Feature Engineering
  • Model Training
  • Model Validation
  • Model Deployment
  • Model Monitoring
  • Anomaly Detection
  • Predictive Maintenance
  • Data Analysis
Soft Skills
  • Communication
  • Problem-Solving
Industry Keywords
  • Utility Networks
  • Telemetry Data
  • SCADA Data
  • Regulatory Compliance
  • Grid Operations
Tools & Technologies
  • Databricks
  • PySpark
  • SQL
  • MLflow
  • Git
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