We are HR Data and Analytics, a centralized global team responsible for all aspects of workforce data strategy, analytics and reporting, data governance, and artificial intelligence and machine learning (AI/ML) based solutions. We are looking for strong industry experience in quantitative and statistical modeling, data mining, insights delivery, and innovative mindset to analyze large-scale multi-dimensional workforce data. You will be a key contributor and collaborator to our intellectual capital by developing intelligent discovery and decisioning tools.

As a Data Scientist Lead - VP, you will be hands-on in analyzing large-scale data to create analytical, statistical, and data science models to uncover underlying patterns and drivers to business questions in employee relations, conduct, security, compliance, customer complaints, etc. This is a highly visible technical role that will interact with multiple internal stakeholders in translating questions into analytical domain, mastering workforce data, implementing solutions, and communicating results. You will embrace a continuous learning and innovation approach in adopting latest tools and technologies.

Job Responsibilities

Design and implement hands-on analytics and explanatory models for workforce data in support of HR and partner business functions’ evidence-based decision.  Build data science, statistical modeling and analytics workflows, from quality checks, feature engineering, to model performance evaluation, and collaborate with technology teams in seamless production deployment. Customize commercial or open-sources analytical solutions and create new algorithms to build proprietary solutions contributing to intellectual capital of the organization. Manage the design, build, and delivery of analytical solutions with a pragmatic approach in evaluating multiple solutions Embrace attention to detail, accountability, rigor, and robustness in data analytics, statistical models, and presenting results to a broad spectrum of stakeholders Capture and understand end-user requirements, translate into customized analytical solutions, communicate results via reports, PowerPoint decks, and insightful visualizations. Articulate complex issues in easy-to-understand ways Understand data life cycles, collaborate with cross-functional teams in business & technology, and leverage capabilities to build repeatable, scalable, and automated products.  Create and document institutional knowledge from workforce data insights, models, and share such knowledge with relevant team members and stakeholders Adhere to various control functions directives, data protection policies, and regulatory requirements while handling proprietary and sensitive data.

Required qualifications, capabilities and skills 

 7+ years’ experience with Bachelors in a related data discipline (e.g., Computer Science, Economics, Business, IO Psychology, Statistics, Business Analytics, or relevant quantitative fields), and/or Master’s degree with 3+ years or equivalent industry experience in a relevant domain. Quantitative and statistical data modeling tools (e.g., Python, R, scikit-learn etc.) to implement a variety of methods (e.g., hypotheses testing, multiple regression, multivariate analyses), exploratory (e.g., clustering, multi-dimensional scaling), anomaly detection, and AI-ML techniques (e.g., supervised / unsupervised / reinforcement learning).   Deep understanding of underlying mathematical concepts and application of statistical pattern recognition (e.g., PCA, correlations), algorithms (e.g., logistic regression, gradient boosting, support vector machines, K-means), model interpretation, cost functions, and performance evaluation (e.g., ROC, hyperparameter tuning) Demonstrated hands-on experience in text mining and NLP analytics, such as customer/employee survey analyses, unstructured data, segment analysis, pattern detection from topic modeling, etc., using variety of commercial or open source techniques Experience in cloud and supporting data analytics frameworks, such as various AWS data processing services, SageMaker, Starburst, Databricks, etc. Intermediate proficiency with reporting and visualization tools (e.g., Tableau, PowerBI) and advanced excel skills (e.g., pivot tables, VLOOKUP, Analysis ToolPak) Demonstrated ability to articulate data insights in business context via customized reports, visualizations, and presentations Versatile in learning and upskilling different software, data processing frameworks, and relevant technologies Relevant experience in consulting, client engagement, or technical project execution with demonstrated experience in leading data & analytics solution delivery

Preferred qualifications, capabilities and skills

Domain knowledge or prior experience in  HR, employee relations, recruitment, compensation, labor market research, customer interaction data preferably in the financial services industry Experience with modern techniques, such as graph databases for network analyses, Generative AI & LLMs Demonstrated experience in learning new areas of focus – especially corporate support functions, compliance, global security, etc., as relates to HR matters Experience managing ambiguity and stakeholder relationships across multiple business functions Experience with project management concepts, such as agile practices, dependency planning, JIRA, etc.