USI Advanced Analytics CL4 (Assistant Manager)
Work Location – Hyderabad
Shift timings: 2:00 to 11:00pm
Talent Experience & Engagement – People Analytics collaborates across Talent areas and the business to uncover analytical insights to help solve business challenges across the talent lifecycle and enable transformational change. Our teams provide a holistic and client-centric approach that complements our wide range of analytical tools and methods to identify valuable workforce insights which, in turn, enable the realization of business objectives and people strategic priorities.
The People Analytics team collaborates closely with stakeholders to: 1) answer research questions that require quantitative and qualitative insights to address complex questions from leaders, 2) understand the sentiment of our people including the strengths and opportunities within their Talent Experience, and 2) evaluate pilots, programs, and services to understand impact and inform improvements. The team leverages existing Talent data, designs and implements custom surveys, and collects qualitative insights from research interviews and focus groups.
People Analytics is looking for an Advanced Analytics Assistant Manager to support the team in executing research-oriented analytics, shaping data-driven actionable insights, and communicating these insights. Through a blend of advanced quantitative and qualitative methods leveraging social science principles, this individual works as part of a team to research and understand complex issues across a wide variety of topics including acquisition, deployment, growth & development, engagement and the talent experience, individual/team performance, and attrition through relevant data. This role is ideal for an intellectually curious, collaborative, and business-savvy analytics expert who thrives at the intersection of data, research, and organizational strategy.
Work you’ll do
- Clean and Structure Data:
- Ensures data accuracy and systematically resolves inconsistencies to maintain high-quality analytical outputs often leveraging SQL, R or Python skills.
- Analyzes Data:
- Designs methodologies that reveal underlying patterns, behaviors, and trends relevant to business and talent challenges, ensuring research rigor and real-world relevance.
- Founded in the principles of social science, employs advanced analytical techniques—including factor analysis, t-tests, regressions, ANOVAs, and correlations—to prepare, refine, and extract insights.
- Collaboration with Data Scientists:
- Works closely with our team data scientists throughout the analytical process—from hypothesis generation and data preparation to model selection and results interpretation.
- Facilitates knowledge exchange and ensures that analytical approaches remain practical, relevant, and actionable for business stakeholders.
- Insight Communication & Storyboarding:
- Synthesize complex analytical results into clear, compelling narratives suited for multiple audiences, including business and talent leaders.
- Develops effective data visualizations and presentations that highlight actionable insights, trends, and recommendations.
Qualifications
- Education: Advanced degree (Master’s, Ph.D., or equivalent) in Social Science, Statistics, Data Science, Economics, Behavioral Science, or a related field strongly preferred.
- Experience: 5-7 years in analytics-focused roles within a consulting, research, or corporate environment, with a proven record of delivering impactful, research-driven insights.
- Technical Skills: Proficiency with statistical modeling tools and languages (e.g., SQL, R, Python, SAS, SPSS), data visualization platforms (e.g., Tableau, Power BI), and data management systems. Demonstrated advanced analytics capabilities such as factor analysis, regression modeling, ANOVA, and correlation analysis.
- Advanced Microsoft Office skills (e.g., PowerPoint, Excel, OneNote, Word, Teams)
- Research Design: Knowledge of social science research methodologies, experimental and quasi-experimental design, survey development, and behavioral analytics.
- Communication: Exceptional ability to translate technical results into business narratives and create compelling presentations.
- Collaboration: Track record of effective cross-functional teamwork, including experience partnering with Data Scientists, business leaders, and external collaborators.
- Strategic Thinking: Demonstrated capacity to frame complex business challenges, set strategic research priorities, and deliver solutions that drive organizational impact.
- Project Management: Strong organizational, planning, and execution skills for managing multiple complex projects with competing deadlines.
- Quality Assurance: Strong attention to detail, experience reviewing and validating analytical approaches, ensuring best practices in data quality and methodological rigor.