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Data Science Phd Jobs (NOW HIRING)

The Director, Data Science will lead efforts across personalization, recommendation systems, and ... Master's Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required.

The Director, Data Science will lead efforts across personalization, recommendation systems, and ... Master's Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required.

The Director, Data Science will lead efforts across personalization, recommendation systems, and ... Master's Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required.

Data Science & Analytics is at the heart of Lyft's products and decision-making. You will leverage ... Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research ...

PhD or Master's in a quantitative field and 8+ years of tech or energy industry work experience as a statistician, quantitative analyst, or data scientist. * 5+ years of experience directly managing ...

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 Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field, or equivalent additional experience. * Experience in Internal Audit, Risk Management, Model Risk ...

PhD in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field, or equivalent additional experience. * Experience in Internal Audit, Risk Management, Model Risk ...

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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.
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What states have the most Data Science Phd jobs? States with the most job openings for Data Science Phd jobs include:
Director, Data Science

Director, Data Science

Gartner

Arlington, VA • On-site

Other

Medical, Retirement, PTO

Re-posted 22 days ago


Job description

About the Role
This is a senior leadership role on the Global Product Management Data Science team managing the Client Experience Digital Platform - the central hub where clients interact with Gartner to unlock value. Our clients are IT and business leaders worldwide, relying on the platform embedded in their workflows for critical priorities. Our mission is to accelerate innovation through intelligent digital products that disrupt the market and ourselves - constantly seeking data science leaders to champion this vision.

The Director, Data Science will lead efforts across personalization, recommendation systems, and GenAI chatbot tools, delivering scalable intelligence that drives hyper-personalized experiences and business outcomes.

What You Will Do

  • Lead the data science roadmap spanning personalization, recommendation systems, and GenAI chatbot development, owning strategy for user profiling, content matching, ranking, conversational AI, and next-best-action systems.
  • Architect AI-powered chatbot systems including intelligent search, recommendation engines, context-aware retrieval, and Model Context Protocol (MCP) servers for seamless AI agent integration with enterprise systems and external tools.
  • Apply transformer-based models, LLMs, and advanced techniques to enhance recommendation relevance, search optimization, user personalization, and scalable GenAI solutions.
  • Leverage internal and external data to model client company priorities, competitive landscapes, engagement signals, and deliver targeted support.
  • Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value.
  • Lead a team of data scientists, driving enhancements in accuracy, coverage, latency, scalability, stability, and adoption while maintaining strong MLOps practices.
  • Translate quantitative analysis into actionable strategies, pitch high-impact ideas, and influence senior leadership on long-term vision and solution roadmaps.
  • Stay current on fast-moving AI/ML advancements, particularly LLMs, conversational AI, agentic systems, and transformer architectures.

What You Will Need

  • 8-12 years of experience in data science, machine learning, or AI, with at least 3 years managing data science and engineering teams.
  • Master's Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required.
  • Proven leadership developing personalization systems, recommendation engines, search/ranking solutions, conversational AI, chatbots, and GenAI applications powered by transformer-based models and LLMs.
  • Demonstrated success translating business priorities into technical roadmaps, driving cross-functional execution, and delivering production ML systems with clear business impact.
  • Strong communication skills to influence executives, translating complex analysis into compelling strategies and value propositions.
  • Deep expertise in ML lifecycle, Lean product principles, MLOps, experimentation frameworks, and production recommender/GenAI systems.
  • Proficiency with Python, ML frameworks (scikit-learn, NLTK, PyTorch, TensorFlow, Hugging Face, LangChain), SQL/relational databases (Oracle), NoSQL/graph databases (MongoDB), vector databases (Pinecone, Weaviate), distributed ML (Spark), Linux/shell scripting, and cloud platforms (AWS SageMaker, Azure ML).
  • Working experience in: Large Language Models/Generative AI, conversational AI/chatbot development, NLP/text mining, search & recommendation systems, prompt engineering/LLM optimization, AI agent architectures.
  • Collaborative leader who thrives in feedback-driven cultures with bias for action and client outcomes.

What You Will Get

  • Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more!
  • Collaborative, team-oriented culture that embraces diversity.
  • Professional development and unlimited growth opportunities.

#LI-CW4

Who are we?

At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world.

Our mission relies on expert analysis and bold ideas to deliver actionable, objective business and technology insights, helping enterprise leaders and their teams succeed with their mission-critical priorities.

Since our founding in 1979, we've grown to 20,000 associates globally who support over 13,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That's why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here.

What makes Gartner a great place to work?

Our vast, virtually untapped market potential offers limitless opportunities - opportunities that may not even exist right now - for you to grow professionally and flourish personally. How far you go is driven by your passion and performance.

We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients.

Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations.

We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work.

Gartner is the world authority on AI

At Gartner, you'll join a company at the very center of the AI revolution. Gartner has proactive, objective guidance throughout clients' AI journeys. We set the standard for how organizations leverage artificial intelligence to drive meaningful impact. You'll have access to unmatched resources, expertise, and technology, and play a key role in helping Gartner and our clients innovate and grow as we leverage AI to transform business and technology landscapes.

It's an exciting time to be at Gartner, with limitless opportunities to make a real impact, grow your skills, and build a lasting, meaningful career in a field that's reshaping the way we operate. If you're passionate about AI and want to be part of a team that's guiding the leaders who shape the world, Gartner is the place for you.

What do we offer?

Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers.

In our hybrid work environment, we provide the flexibility and support for you to thrive - working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring.

Ready to grow your career with Gartner? Join us.

Gartner believes in fair and equitable pay. A reasonable estimate of the base salary range for this role is 122,000 USD - 168,000 USD. Please note that actual salaries may vary within the range, or be above or below the range, based on factors including, but not limited to, education, training, experience, professional achievement, business need, and location. In addition to base salary, employees will participate in either an annual bonus plan based on company and individual performance, or a role-based, uncapped sales incentive plan. Our talent acquisition team will provide the specific opportunity on our bonus or incentive programs to eligible candidates. We also offer market leading benefit programs including generous PTO, a 401k match up to $7,200 per year, the opportunity to purchase company stock at a discount, and more.


The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity.

Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company's career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email toApplicantAccommodations@gartner.com.

Job Requisition ID:108588

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