Data Scientist
hace 7 meses
**Who we are and what we do**
Deel is a global team that helps businesses hire anyone, anywhere, easily. Deel consists of more than two thousand self-driven individuals spanning over 100 countries. Our unified yet diverse culture keeps us continually learning and innovating the Deel platform and our products for customers.
Companies should be able to hire the best talent anywhere in the world, so we are building the best platform to make that a reality. Our market-leading technology, expertise, and global team are crucial to the success of Deel’s platform. We deliver the best products and platform features in our space, enabling millions of jobs worldwide and connecting the global workforce with the best companies and opportunities.
**Why should you be part of Deel's success story?**
We offer global teams all the tools they need to hire, onboard, manage, pay, and scale at full speed. We aim to foster a diverse global economy by building a generational platform that seamlessly connects companies with talent worldwide.
After our successful Series D in 2021, we raised another $50M last year, doubling our valuation to $12B.
There’s never been a more exciting time to join Deel — the market leader in international payroll and compliance.
**Responsibilities**:
- Problem Definition and Research:
- Collaborate with cross-functional teams to understand business objectives and identify opportunities for leveraging data to drive solutions
- Define and clarify the problem or question being addressed through data analysis
- Data Collection and Integration:
- Source, collect, and integrate structured and unstructured data from various internal and external sources
- Collaborate with People Data team to ensure data quality, consistency, and reliability
- Data Exploration and Preprocessing:
- Explore and analyze data to discover patterns, trends, and insights using statistical and exploratory data analysis techniques
- Preprocess and clean data to address missing values, outliers, and other data quality issues
- Feature Engineering:
- Develop and engineer relevant features from raw data to enhance the performance of machine learning models
- Collaborate with experts to identify and incorporate features
- Model Development:
- Develop and implement advanced statistical models and machine learning algorithms to analyze people-related data, including recruitment, employee engagement, performance, and retention
- Utilize predictive analytics to forecast talent needs, identify high-potential employees, and optimize employee development programs
- Optimize and fine-tune models for performance, scalability, and interpretability
- Stay abreast of the latest advancements in machine learning and incorporate relevant techniques into model development
- Model Evaluation and Validation:
- Design and conduct experiments to uncover patterns, trends, and correlations in people data, translating findings into actionable recommendations for strategic planning
- Evaluate model performance using appropriate metrics and statistical methods
- Validate models for accuracy, reliability, and generalizability
- Implement strategies for continuous model monitoring and improvement
- Data Visualization and Communication:
- Create compelling visualizations to communicate complex findings and insights to both technical and non-technical stakeholders
- Effectively communicate results and methodologies through reports, presentations, and documentation
- Build and maintain dashboards and reports to communicate insights and key performance indicators related to people metrics
- Collaborative Work:
- Work closely with cross-functional teams, including business analysts, engineers, and domain experts, to integrate data science solutions into processes
- Collaborate with IT and security teams to ensure data privacy and compliance with regulatory standards
- Research and Development:
- Stay abreast of HR industry trends and advancements in data science methodologies, contributing to continuous improvement and innovation within the organization
- Engage in research and development activities to enhance the team’s data science capabilities
**Qualifications**:
- English fluency - conversational and professional writing
- Advanced degree in Data Science, Statistics, Computer Science, or a related field.
- Knowledge of trends and developments in data management and security preferred
- Strong understanding of GDPR data compliance
- Strong business acumen and analytical skills for data visualization and storytelling efforts that translate into digestible insights and actionable recommendations
- Advanced SQL or equivalent skills relating to scalable data transformation
- Experienced in developing reporting and dashboards with BI tools such as Looker or similar
- Experienced in regression analysis and other statistical modeling techniques
- Ability to partner, collaborate with, and influence relevant stakeholders across diverse functions and e
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