Skill required: Reporting & Advisory - Reporting Analytics

Designation: Analytics and Modeling Senior Analyst

Qualifications:Any Graduation

Years of Experience:5 to 8 years

About Accenture

Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com

What would you do

As a HR Data Science Senior Analyst, you will be part of the BI&A Business Insights & Analytics team focused on HR & responsible for providing Accenture business & HR leaders with strategic & operational analytics and insights to enable data-led decision making. This will involve collecting, analyzing, and interpreting data leveraging AI to identify trends and patterns that can help us improve employee performance.
The Data Science Analyst supports the development and delivery of advanced analytics, machine learning, and AI-driven solutions that help solve complex workforce and business challenges. The role involves analyzing large and often unstructured datasets, building predictive and prescriptive models, and generating actionable insights that enable data-driven decision-making.
Key Skills & Technical Expertise
Proficiency in Python and SQL for data extraction, transformation, analysis, and model development.
Experience with data manipulation and analytical libraries such as Pandas, NumPy, Scikit-learn, and related tools.
Experience working with BigQuery and cloud-based analytics platforms.
Knowledge of Google Cloud Platform-GCP preferred. What are we looking for
Strong understanding of statistical analysis, predictive modeling & machine learning techniques.
Experience developing and deploying machine learning models, including feature engineering, model validation, performance monitoring.
Knowledge of forecasting, classification, regression, clustering & optimization techniques.
Familiarity with deep learning, Natural Language Processing-NLP & text analytics.
Hands-on experience with Generative AI, Large Language Models-LLMs,Agentic AI applications.
Understanding of Responsible AI principles, model governanceðical AI practices. Roles and Responsibilities:
Key Responsibilities
Perform data mining, exploratory data analysis-EDA, and data preparation on large and complex datasets from multiple sources.
Develop, validate, and deploy statistical, machine learning, and AI-driven models to address workforce and business challenges.
Apply advanced analytics techniques to generate predictive and prescriptive insights that support strategic decision-making.
Build and enhance analytics solutions using modern Data Science, Machine Learning, Generative AI, and Agentic AI methodologies.
Utilize Python, SQL, and cloud-based technologies to extract, transform, analyze, and model data efficiently.
Develop automated reporting, insight-generation solutions, and AI-powered analytical tools to improve business outcomes.
Ensure data quality, model accuracy, and adherence to responsible AI and data governance principles.
Stay current with emerging trends in Data Science, AI, machine learning, and workforce analytics.
Work independently on routine assignments while receiving guidance on more complex projects and new initiatives.
Qualifications
Master s degree in Data Science, Statistics, Economics, Econometrics, Computer Science, Business Analytics, Operations Research, or a related quantitative field.
3+ years of experience in Data Science, Analytics, People Analytics, Workforce Analytics, or a related analytical role.
Demonstrated experience in building analytical models and translating insights into business recommendations.
Experience working with large, structured, and unstructured datasets.