What you will do:
- Work on Data science projects in close collaboration with the Data Engineering team, Application development team, Product owners and business leaders to deliver high value business capabilities
- Solve ‘Search’ value stream problems and help improve Gartner’s client experience in finding the most meaningful and valuable insights
- Build user query understanding and intent refinement models to refine query to content similarity
- Build and incorporate LLMs in addition to vector search capabilities
- Be responsible for high quality data science solutions with respect to accuracy and coverage.
- Be accountable for solutions’ scalability, stability, and business adoption
- Responsible for maintaining proper documentation and further code-reusability principles
- Responsible for ownership of algorithms and its enhancements/optimizations as per business requirement
- Collaborate with Director, Data Science in long term vision, strategy, and solution roadmap to align with bigger business objectives and mission critical priorities of the organization
- Responsible to pitch ideas, present solutions and influence senior leaders with strong business value propositions
- Stay on top of fast-moving AI/ML models and technologies. Understand and follow disruptive data science solutions
- Collaborate with engineering and product teams to launch MVPs and iterate quickly
- Independently plan and drive data science projects that deliver clear business value
What you will need:
- 6-8 years hands-on experience building predictive models, search systems, or other machine learning/artificial intelligence applications to drive business impact
- Bachelor’s degree required while a master’s degree in a quantitative field (math, computer science, engineering, etc.) is strongly preferred
- Demonstrated ability to translate quantitative analysis into actionable business strategies.
- Strong communication skills in technical and business domains
- Working experience in some of the following data science areas:
- Machine Learning and Predictive modeling
- Text mining and Natural Language Processing
- Search or Recommendation systems
- Data analytics with multi-dimensional data
- Generative models
- Strong working knowledge of Lean product principles, software development lifecycle, and machine learning life cycle
- Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies
- Ability to implement latest ML research to improve our current algorithms
- Experience and proficiency with Python, machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning (e.g., pytorch, tensorflow), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databases (e.g., MongoDB, graph database), distributed machine learning (spark), Linux and shell scripting
- Experience with cloud computing services such as AWS or Azure ML
- Ability to work collaboratively across product, data science and technical stakeholders
- Ability to work in a culture that thrives on feedback and seeks opportunities to stretch outside comfort zone
- Bias for action and client outcome oriented