About Workforce AI: Workforce AI is an innovative startup dedicated to transforming how businesses understand and leverage their human capital. We develop cutting-edge Machine Learning and Artificial Intelligence models to provide deep insights into labor availability, potential, and strategic planning, ultimately optimizing operational efficiency and growth for our clients. We are currently in an exciting pre-seed phase, building out our foundational models and seeking passionate individuals to join our mission.

The Opportunity: Are you an aspiring data scientist eager to gain hands-on experience building impactful AI/ML models in a dynamic startup environment? Workforce AI is seeking a highly motivated and talented Junior Data Scientist to join our team on a part-time, unpaid basis. This is a unique opportunity to contribute significantly to our core product development, work alongside experienced professionals, and build a strong portfolio. While this role is initially unpaid, it carries significant potential to transition into a full-time, paid position upon successful Series A funding.

What You'll Do: As a Junior Data Scientist, you will play a crucial role in developing and refining our core AI/ML models. Your responsibilities will include:

Data Collection & Preprocessing: Assisting in identifying, collecting, cleaning, and transforming diverse datasets relevant to labor market dynamics, workforce demographics, and operational data.
Model Development: Contributing to the design, implementation, and training of various machine learning and optimization models (e.g., predictive models, classification algorithms, natural language processing models, optimization models) to address specific business problems related to workforce intelligence.
Feature Engineering: Collaborating on identifying and creating new features from raw data to improve model performance and interpretability.
Model Evaluation & Optimization: Performing rigorous evaluation of model performance using appropriate metrics, identifying areas for improvement, and implementing optimization strategies.
Model Deployment: work on pipelines to deploy science models for production, including packaging, testing, and integrating them into scalable, real-world applications
Experimentation: Designing and executing experiments to test different modeling approaches and hypotheses.
Documentation: Documenting model architecture, methodologies, and findings for internal knowledge sharing and future development.
Research: Staying up-to-date with the latest advancements in AI/ML, particularly in areas relevant to labor economics and human resources.
Collaboration: Working closely with the founding team to understand project requirements, provide technical insights, and contribute to strategic discussions.

What We're Looking For:

Education: Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
Technical Skills:
Proficiency in Python and relevant data science libraries (e.g., scikit-learn, pandas, NumPy, matplotlib, seaborn).
Familiarity with experiment design and optimization algorithms (i.e. facility location problems)
Basic understanding of SQL for data extraction and manipulation.
Proficiency in statistical concepts and machine learning algorithms (e.g., regression, classification, clustering, time series analysis).
Problem-Solving: Strong analytical and problem-solving skills with a keen eye for detail.
Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts clearly.
Proactiveness & Self-Motivation: Ability to work independently, take initiative, and thrive in a fast-paced, ambiguous startup environment.
Passion: Genuine interest in AI/ML and its application to workforce dynamics and operational efficiency.
Availability: Ability to commit approximately 10-20 hours per week.

Why Join Workforce AI?

Impact: Make a tangible impact on the development of innovative AI/ML solutions from the ground up.
Experience: Gain invaluable hands-on experience in a real-world data science environment, building practical models.
Mentorship: Work closely with and learn from experienced professionals in the AI/ML and business strategy domains.
Growth Potential: Significant opportunity to transition into a full-time, paid role with equity upon successful Series A funding.
Portfolio Building: Build a strong portfolio of practical AI/ML projects.
Flexible Work: This is a remote-friendly role with flexible hours
To Apply: Please submit your resume and a brief cover letter outlining your interest in this role [email protected], your relevant experience. Please also include links to any relevant projects (e.g., GitHub, Kaggle) that showcase your data science skills.

Data scientist