Data Scientist

March 5

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Lightcast

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Lightcast is a leading authority on labor market data, providing trusted and comprehensive labor market analytics to drive decisions across education, enterprise, and government sectors. With more than 23 years of experience, Lightcast delivers detailed insights into skills, jobs, supply and demand through an extensive data set generated from millions of job postings, career profiles, and other sources across the globe. Their services are designed to help educational institutions, enterprises, and government organizations build future-ready workforces by using AI-enabled and continuously updated data. Lightcast is globally recognized and trusted by industry innovators, and is a vital resource for organizations navigating workforce challenges and demographic changes in the labor market.

Economic Development • Labor Market Data • Economic Impact Analysis • Business Development • Higher Education

501 - 1000 employees

🏢 Enterprise

📚 Education

🏛️ Government

📋 Description

• The Data Scientist will work closely with the Product, Data, and Research teams to analyze labor market trends, workforce dynamics, and economic patterns. • The role involves cleaning, organizing, and interpreting large-scale datasets to develop innovative models, datasets, and visualizations that provide actionable insights into the future of work. • The ideal candidate will demonstrate strong statistical thinking, a solid grasp of machine learning principles, and the ability to apply core methodologies such as predictive modeling, econometric analysis, and time series forecasting. • This position requires a collaborative mindset to work cross-functionally, ensuring the seamless integration of analytical insights into Lightcast's products and services.

🎯 Requirements

• Bachelor's or Master’s degree in Data Science, Statistics, Economics, Computer Science, or a related quantitative field. • 2+ years of industry or graduate research experience solving analytical problems and building models using quantitative, statistical or machine learning approaches. • Proficiency in Python, SQL, and machine learning frameworks (e.g., Scikit-Learn, PyTorch). Strong programming skills are essential, with the ability to write clean, scalable code and independently build prototypes for new ideas. • Practical knowledge across various machine learning techniques, such as classification, regression, and time-series forecasting. • Experience with cloud platforms (e.g., AWS) and the ability to manage and streamline large datasets efficiently (e.g., using tools like Apache Airflow) • Keen statistical thinking ability and excels at turning data into strategic insights • Excellent interpersonal, written and verbal communication skills, with particular ability to convey technical information to a variety of technical and non-technical audiences