Data Scientist - Desde casa, Colombia - Deel

Deel

Empresa verificada

Desde casa, Colombia

hace 1 semana

Publicado por:

Carolina González

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Descripción

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 crossfunctional 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 peoplerelated data, including recruitment, employee engagement, performance, and retention
Utilize predictive analytics to forecast talent needs, identify highpotential employees, and optimize employee development programs
Optimize and finetune 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 nontechnical 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 crossfunctional 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