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The Sr People Scientist is responsible for supplying to the development of an enterprise-wide people science vision and research science roadmap for T-Mobile. This role involves identifying and addressing sophisticated business problems related to employee experience, talent, and organizational capability/efficiency. The Sr People Scientist will own and complete end-to-end research science projects as a part of long-term planning for developing and integrating diverse data sources for complex modeling and support scalable processes for large-scale data analysis and AI/ML model development.
Job Responsibility:
Support the vision and research science roadmap in collaboration with the HR leadership team and senior leadership partners
Collaborate in identifying and addressing large-scale, sophisticated business problems related to employee experience, talent, and organizational capability
Drive the development and integration of diverse and complex data sources for advanced and sophisticated qualitative and quantitative modeling
Contribute to maintaining high standards in research science, including supporting the mentoring and development of team members
Develop and implement network analytics, AI/ML, and Deep Learning models to analyze sophisticated datasets and support innovation in people science
Build and run true A/B and quasi-experimental designs to assess the impact of mechanisms, programs, and various tested solutions that align to the overall T-Mobile people strategy
evaluate research initiatives to provide bottom line value, return on investment and improvements
Translate technical research findings into clear, concise, and engaging reports that support decisions and applications across the employee lifecycle
Collaborate with multiple teams and account teams to influence, build consensus, and drive significant T-Mobile wide changes related to applying research science proposals and recommendations, including changes to programs, engineering and system needs, and people strategy roadmaps
Master's/Advanced Degree Quantitative Subject area (I-O Psychology
Behavioral Economics
Applied Social Psychology w/emphases on research science and advanced statistics)
Doctorate Quantitative Discipline (I-O Psychology
Behavioral Economics
Applied Social Psychology w/emphases on research science and advanced statistics)
7-10 years Research science or related experience
Proven experience with Gen AI for foundational models and LLM and demonstrating for analytics
4-7 years Combination of deep technical skills and business savvy to interface and influence all levels and fields
7-10 years Strong interpersonal skills to optimally advocate technical solutions to business audiences, HR executives, and tech teams
4-7 years Familiar with one or more program languages such as Python, C#/C+, Java, or Perl
Demonstrated ability building and deploying true and quasi-experimental research designs that pragmatically land with the business
4-7 years Proven experience in predictive modeling, network analysis, building and deploying AI/ML models and hands on experience developing deep learning models
4-7 years Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations
4-7 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
4-7 years Experience with statistical methods and sophisticated modeling techniques. For example- SVM, Random Forest, graph models, Bayesian inference, NLP, Computer Vision, neural networks
Demonstrated ability with data scripting languages (e.g., SQL, Python, R)
Proven experience in data visualization
4-7 years Extended experience working with relational database using SQL
2-4 years Experience in tech industry
Strategic Planning Ability to build a long-term roadmap and 12 month plans
Executive Communications Skills in presenting effectively to Director and above leaders and influencing executive partners
Analytics Skill in analyzing passive and active network data
Design Research Knowledge and skills for crafting A/B tests and quasi-experimental designs
Mathematics Calculus, linear algebra, statistics, and probability
Programming Proficiency in Python and SQL
Machine Learning: Apply machine learning techniques including supervised and unsupervised learning
collaborative filtering
and artificial neural networks
Deep Learning: Research, design, implement, evaluate, and optimize novel algorithms/models in Deep Learning space
Communication Outstanding communication skills, ability to work with cross functional teams
Nice to have:
Familiar with one or more program languages such as Python, C#/C+, Java, or Perl
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