About this Role : 

This role will have equal part people management and individual contributor responsibilities. As a Director you will be responsible for managing a small team largely working on projects focused on improving the quantity and quality of data, we obtain from client interactions. The team will be responsible for bringing a business lens to this data asset, in order to identify high-value use cases for client interaction data; then pilot, scale and operationalize them in partnership with the IT team. Given the data assets, you will need experience in using NLP techniques to extract insights from quantitative and text (like call transcripts) data.

Technical Responsibilities:

- Develop and leverage data science algorithms to draw insights from Gartner internal and external data assets to be used in research content and planning

- Responsible for problem structuring, solutioning and ensuring quality of the solution in terms of industry standard best practice and quality metrics

- Technical solution design of different AI/ML-based projects and executing them to ensure a reliable, scalable, maintainable solution.

Indicative Projects:

- Apply Natural Language Processing on client call transcripts to extract key concepts and themes being discussed, identify the intent, key question being asked and map the discussion topics to internal research taxonomy

- Use Machine Learning to develop self-correcting algorithms to cluster topics being discussed in calls to draw meaningful insights

People and Talent Management:

- People Manager of Data Scientists and Analytics experts

- Manage and mentor associates in the team to level up with respect to technical skills and soft skills. Coach high performing associates for the next level

- Act as guide for Analytics and Data Science projects across other teams in Gartner

Process Management:

Introduction of coding standards, code reviews, peer reviews, ensuring code reusability, providing technical feedback, ensuring solution design is documented and ensuring these processes are followed.

Partnering/Collaboration:

IT team: Closely partner and collaborate with the technology and data engineering team for creating automated Data science pipeline to productionize the solutions.

R&A Practices: Partner with practice area leadership to understand their mission-critical research priorities and make staffing and resourcing decisions that maximizes team impact. Also, work with Data Scientists in Practices to standardize analytics approaches and partner on high impact projects.

What You'll Need:

- 12+ years of industry experience with 5+ years of hands-on AI or ML system development experience on real-world industry problems, with focus on Text Mining and Natural Language Processing

- 3+ years of experience in managing teams working on analytics / data science projects

- Bachelor's degree or higher in computer science, applied statistics or equivalent

- Hands on experience in executing NLP & text mining projects using tools like Python/R & machine learning techniques like Topic Modelling, SVM Classification, Named Entity Recognition, Part of Speech Tagging, Sentiment Analysis, Information Extraction, etc

- Hands on experience in handling unstructured data sources such as notes, documents, emails, chats & call transcripts will be an advantage

- Experience working with or collaborating with data engineering/IT Data Science team for creating automated Data pipeline to productionize analytics solutions will be an advantage

- Working knowledge in statistical modeling methods for supervised and unsupervised learning.

What we offer

- Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Employee Provident Fund (EPF) contributions, Parental Leave, Employee Assistance Program (EAP) and more!

- Collaborative, team-oriented culture that embraces diversity

- Professional development and unlimited growth opportunities

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