Data Scientist
AI in this role
About the role:
The Data Scientist - Peer Content Analytics is a hands-on technical expert responsible for designing, building, and deploying machine learning, NLP, and AI solutions. You’ll work at the crossroads of data science, content strategy, and product innovation, turning large volumes of structured and unstructured data into actionable intelligence that drives strategic decisions.
You will collaborate with Content Strategy, Business & Technology Insights (BTI), Product, and Engineering teams to identify high-impact opportunities, operationalize advanced analytics, and translate experimental findings into clear, compelling business narratives that drive strategic decision-making.
What You'll Do:
Advanced Analytics & AI Solutions:
Develop, deploy, and maintain scalable machine learning, NLP, and generative AI models using data from Gartner Peer Insights and Peer Community platforms.
Build reusable pipelines for sentiment analysis, topic modeling, LLM-based summarization, clustering, and other AI-driven content solutions.
Explore and analyze complex datasets to uncover trends, patterns, and actionable signals that inform research and content strategy.
Methodology & Experimentation:
Design, implement, and refine scoring systems, ranking algorithms, and statistical models for peer-driven content and publications.
Establish robust experimentation frameworks, define success metrics, and ensure findings are statistically sound.
Apply advanced statistical techniques for bias detection, hypothesis testing, regression, and A/B testing.
Cross-Functional Collaboration:
Partner with business stakeholders to identify opportunities for differentiated peer-driven insights and translate model outputs into actionable narratives for published insights.
Collaborate with DPT and Engineering to design data pipelines and infrastructure that support model use cases and cross-tool integrations.
Present complex analytical concepts and model outcomes to non-technical stakeholders in a clear and engaging manner.
Visualization & Reporting:
Leverage PowerBI to create interactive dashboards and self-service reports that make complex data accessible to a broad audience.
Ensure data products are well-documented, version-controlled, and tested for reliability and reproducibility.
What You'll Need:
Bachelor’s degree required; Master’s degree in a quantitative field (Math, Computer Science, Engineering, Economics, etc.) strongly preferred.
2-4 years of hands-on experience in data science or applied ML (predictive modelling), with a proven track record of delivering end-to-end solutions in a business environment.
Demonstrated ability to translate business objectives into actionable data science projects and quantitative analysis into strategic business recommendations.
Advanced proficiency in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL for data extraction, transformation, and validation.
Deep experience in NLP, including topic modeling, sentiment analysis text classification, and semantic similarity.
Hands-on experience with LLMs and generative AI frameworks, including cloud deployment on Azure or AWS.
Experience with MLOps best practices, experiment tracking (MLflow, Weights & Biases), and production monitoring.
Advanced PowerBI skills for data visualization and interactive reporting.
Excellent communication and collaboration skills, with a proven ability to present complex modeling decisions and data insights to non-technical audiences.
Experience in methodology design for content products, including creating consistent rules for ranking, scoring, or evaluating products and companies.
Proven ability to proactively identify data-driven content opportunities and rapidly convert insights into impactful content.
Added Advantage: Experience in building, deploying, or enhancing chatbot solutions using NLP and LLM technologies.
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.
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 to ApplicantAccommodations@gartner.com.
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How we rate this
Data Scientist at Gartner rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used TensorFlow hands-on?
- Walk me through how you've used scikit-learn in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: ML Ops, NLP, PyTorch, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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