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Data Science Phd Jobs in Spring, TX (NOW HIRING)

Hexagon AB

Lead Data Scientist

Houston, TX · On-site

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD preferred) * Track record of deploying ML systems processing large-scale datasets with proper ...

United Airlines

Associate Data Scientist

Houston, TX

$75K - $90K/yr

Minimum of 15 months of professional (non-internship) work experience in data science, AI, or ... Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD). Experience with ...

Hp

Principal AI Data Scientist

Spring, TX · On-site

$147K - $230K/yr

Responsibilities Leads organization-wide team or teams of other data science professionals in ... PhD related to AI and 5+ years of experience or Master's degree related to AI and 10+ years of ...

bp

Digital science associate

Houston, TX · On-site

... Data Science, Applied Mathematics, Physics, Chemical Engineering, Mechanical Engineering, Computational Science, Engineering, or a related technical field. * PhD or equivalent experience research ...

Microvast

BMS Data Analysis Engineer

Houston, TX · On-site

$109K - $131K/yr

Required : • Master's or PhD in Computer Science, Mathematics, Engineering, or a related field. • 2-5 years of experience in data analysis, preferably in battery systems, energy storage, or ...

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Data Science Phd information

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 the key skills and qualifications needed to thrive as a data science PhD?

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.

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.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What job categories do people searching Data Science Phd jobs in Spring, TX look for?

The top searched job categories for Data Science Phd jobs in Spring, TX are:

What cities near Spring, TX are hiring for Data Science Phd jobs?

Cities near Spring, TX with the most Data Science Phd job openings:

Data Science Phd jobs near you
Infographic showing various Data Science Phd job openings in Spring, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Lead Data Scientist

Houston, TX • On-site

Hexagon AB
501 - 1,000 employees
Learn more about Hexagon ABexternal

Full-time

Re-posted 22 days ago

Job description

Lead Data Scientist
Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA | Roanoke, Virginia-USA
Workplace Type: Remote
Req Id: 2289
Responsibilities
Octave's ETQ division is seeking a hands-on Data Scientist to build predictive models, implement Generative AI and Agentic AI features, and architect data-driven solutions for our document-based compliance management platform. This role requires a technical expert who can develop, deploy, and maintain ML systems in production environments.
  • Build and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and RAG architectures with vector databases for compliance document understanding
  • Design agentic AI systems that autonomously handle compliance workflows, document review, regulatory mapping, and multi-step reasoning tasks
  • Implement comprehensive LLM evaluation frameworks with automated pipelines, custom metrics, benchmark datasets, and safety guardrails ensuring regulatory compliance
  • Build end-to-end MLOps pipelines for model training, deployment, monitoring, versioning, and automated retraining with drift detection
  • Develop predictive models for compliance risk scoring, regulatory change impact, anomaly detection, and time-series forecasting
  • Write production-quality Python code for data processing, feature engineering, API development (FastAPI/Flask), and ETL/ELT workflows
  • Lead A/B experiments and product analytics to measure AI feature impact and drive data-driven decision-making
  • Create explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency and regulatory adherence
  • Collaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders

Python (5+ years): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest
SQL: Advanced proficiency with complex queries, window functions, and optimization
Machine Learning & NLP: Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis
Generative AI & LLMs: Hands-on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma)
MLOps & ModelOps: End-to-end experience with ML pipelines, experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, CI/CD for ML, and Docker containerization
LLM Evaluation: Experience with evaluation frameworks (RAGAS, DeepEval), custom metrics, benchmark datasets, and human-in-the-loop validation
Cloud & AWS: Experience with AWS services including SageMaker, Bedrock, S3, Lambda, EC2, and CloudWatch
Statistics & Experimentation: Strong foundation in statistics, A/B testing, causal inference, and experimental design
Visualization: Proficiency with Tableau, Power BI, or Python visualization libraries
Education / Qualifications
Experience & Education
  • 7+ years in data science, ML engineering, or related roles
  • 3+ years building NLP/generative AI applications and implementing MLOps in production
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD preferred)
  • Track record of deploying ML systems processing large-scale datasets with proper monitoring and governance

Preferred Qualifications
  • Experience with agentic AI frameworks (LangGraph, LangChain, AutoGen, CrewAI)
  • Knowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems
  • Familiarity with big data tools (Spark, Databricks, Snowflake), orchestration (Airflow, Kubeflow), and monitoring tools (Datadog, Prometheus)
  • Experience with LLM fine-tuning, document processing libraries, multi-modal AI, or distributed training
  • Understanding of ML governance, bias detection, model risk management, and data privacy regulations (GDPR, CCPA, HIPAA)
  • Experience working in agile environments with Jira
  • AWS ML certifications or similar credentials

Key Competencies
  • Strong communication skills explaining complex models to technical and non-technical audiences
  • Ability to work independently and collaboratively in fast-paced environments
  • Proven ability to convert POCs into production-grade solutions
  • Understanding of ethical AI and building trustworthy, explainable systems for regulated environments

#LI-PB1 LI-Remote
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About Octave
Octave provides mission-critical software that empowers organizations to make informed decisions across every stage of the asset lifecycle - Design, Build, Operate and Protect - where performance, safety, and reliability are non-negotiable and failure is not an option.
Turning complex operational data into actionable intelligence, Octave connects expertise, real-world conditions and enterprise-scale insight to improve performance, resilience and incident response where it matters most.
Octave has approximately 7,200 employees in 45 countries. Learn more at octave.com and follow us on LinkedIn.
Why work for Octave?
All in. Always forward. That's the way we do things around here. We put trust in our people because we believe it's the best way to unleash potential, bring ideas to life, and keep moving ahead. And it's why we're committed to creating an environment that's truly supportive, providing you with the resources you need to support your ambitions, no matter who you are or where you are in the world.
Everyone is welcome
At Octave, we believe that diverse and inclusive teams are critical to the success of our people and our business. Here, everyone is welcome. As an inclusive workplace, we don't discriminate. In fact, we embrace differences and are fully committed to creating equal opportunities, an inclusive environment, and fairness for all.
Respect is the cornerstone of how we operate, so speak up and be yourself. You're valued here.
Recruitment Fraud Alert
Octave posts all official job opportunities on either https://careers.octave.com/ or https://www.octave.com/about/careers and communicates only from email addresses ending in @octave.com. We never request payment or personal banking information during recruitment. No offers will ever be extended without a proper interview via Teams or in person, never done over email alone. If you suspect fraud, it probably is, and contact us at careers@octave.com

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