Data Scientist

About The Role
The Data Scientist - Peer Content Analytics serves as a technical expert tasked with designing, building, and deploying cutting-edge ML, NLP, and AI solutions. You will operate at the intersection of data science, content strategy, and product innovation, converting large volumes of structured and unstructured data into actionable intelligence that shapes strategic decisions.
Key Responsibilities
- Advanced Analytics & AI Solutions: Develop, deploy, and maintain scalable machine learning, NLP, and generative AI models utilizing 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.
- Data Exploration: 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. Establish robust experimentation frameworks with defined success metrics. Apply advanced statistical techniques including bias detection, hypothesis testing, regression, and A/B testing.
Cross-Functional Collaboration
- Partner with business stakeholders to identify opportunities for differentiated insights and translate model outputs into actionable narratives. Collaborate with DPT and Engineering teams on data pipelines supporting cross-tool integrations. Present complex analytical concepts and outcomes to non-technical audiences clearly and engagingly.
Visualization & Reporting
- Leverage PowerBI to create interactive dashboards and self-service reports for broad audience accessibility. Ensure all data products are well-documented, version-controlled, tested for reliability, and reproducible.
Requirements
- Bachelor's degree required; Master's in a quantitative field (Math, Computer Science, Engineering, Economics) strongly preferred.
- 2-4 years of hands-on experience in data science or applied ML with a proven track record of delivering end-to-end solutions in a business environment.
- Ability to translate business objectives into actionable projects and analysis into strategic 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 deployed 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 skills to present modeling decisions to non-technical audiences.
- Experience in methodology design for content products including consistent rules for ranking and scoring.
Preferred Qualifications
- Experience building, deploying, or enhancing chatbot solutions using NLP and LLM technologies.