Lead Data Scientist - HR Focus (Only G.C / U.S.C)
6+Months
New York, NY (Onsite)
**Objectives**:
The main goal of this role is to apply data science methodologies and HR domain knowledge to enhance human resource management through predictive analysis, machine learning, and big data techniques.
**Key Responsibilities**:
- Design, develop, and implement end-to-end data analytics solutions to address HR-related challenges and drive organizational effectiveness.
- Lead a team of data scientists and analysts, fostering a collaborative environment and ensuring the delivery of high-quality data-driven insights.
- Work closely with HR stakeholders to understand their needs and translate business problems into analytical frameworks.
- Spearhead the creation and the refinement of predictive models for HR-related outcomes such as employee attrition, hiring success, and talent development.
- Drive innovation by exploring new data sources and advanced analytics methods to continuously improve HR decision-making processes.
- Disseminate findings and recommendations to senior leadership through compelling presentations and reports.
**Qualifications and Skills**:
- Advanced degree (Master''s or PhD) in Data Science, Statistics, Computer Science, or a related quantitative field.
- Proven expertise in HR analytics, workforce analytics, or relevant field with a minimum of 5 years of experience in a data science role, including leadership responsibilities.
- Strong proficiency with statistical programming languages such as R, Python, or similar tools.
- Experience with machine learning, predictive modeling, and big data platforms.
- Excellent understanding of HR processes, systems, and data sources.
- Demonstrated ability to manage cross-functional projects and lead a team towards achieving business goals.
- Outstanding communication and interpersonal skills, with the ability to articulate complex data insights to non-technical audiences.
**Working Environment**: The individual will be expected to work in a dynamic and collaborative professional setting, interfacing with various levels of management and team members across the organization.
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