Data Scientist or Associate Data Scientist

About the role:
This is a unique opportunity to join our fast-growing Data Science team. In the role of Data Scientist/ Associate Data Scientist in Client Retention Analytics team, you will execute large scale, high impact data modeling projects with responsibility for designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. This person will have a flair of innovation along with a strong exposure to Classical ML, Python, NLP, statistical principles and their application in modeling.

What You Will Do:

• Deliver ad hoc modeling and advanced analytical insights to drive strategic and operational decision-making across the organization
• Lead all phases of the DS project lifecycle, including: understanding complex business challenges, proposing and architecting technical solutions, data wrangling, data cleaning, exploratory data analysis, feature engineering, model selection and development, rigorous model validation, operationalization, and deployment of models, as well as the clear presentation and documentation of results and actionable insights
• Effectively communicate complex technical solutions and analytical results to both technical and non-technical stakeholders, ensuring alignment and understanding
• Collaborate cross-functionally with business stakeholders, IT, and Project Management teams to design, develop, and deliver cutting-edge analytics solutions that have a measurable business impact.
• Leverage the latest technologies and methodologies, including Machine Learning, Artificial Intelligence, Natural Language Processing (NLP), and advanced Statistical Modeling, to solve challenging business problems
• Integrate advanced NLP techniques such as vector databases (VectorDB), embeddings, topic modeling, and fine-tuning of transformer models like BERT to enhance text analytics capabilities

What You Will Need:

• Candidates with 3-6 years (for Data Scientist) OR 1-3 years (for Associate Data Scientist) of professional Data Science experience must hold a Bachelor's or Master's degree in Statistics, Data Science, Computer Science, or a related field
• Deep understanding of statistical principles and their practical application in data modeling and analysis
• Proven experience developing and deploying descriptive, predictive, and prescriptive models
• Advanced knowledge and practical expertise in NLP, including experience with vector databases, embeddings, topic modeling, and fine-tuning transformer-based models such as BERT
• Experience with using GenAI models (GPT4 etc.) is good to have
• Proficiency in Python, SQL, and Spark; working knowledge of Power BI, Excel, and PowerPoint
• Hands-on experience with a variety of modeling techniques, including but not limited to: Time Series Analysis, Random Forests, Clustering, Neural Networks, Generalized Linear Models, Optimization, Design of Experiments (DOE), and Dimensionality Reduction
• Experience in key business applications such as churn analysis, customer profiling, and recommendation systems
• Ability to thrive in a fast-paced environment, managing multiple priorities and delivering high-quality results within established timelines
• Exceptional communication skills, with the ability to convey complex technical concepts to diverse audiences and influence key stakeholders and leaders across the organization

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

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 insight, helping enterprise leaders and their teams succeed with their mission-critical priorities.

Since our founding in 1979, we've grown to more than 21,000 associates globally who support ~14,000 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 sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. 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.

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.

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