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Data Scientist at Lightcast. Location Information: Remote (Work From Home) US. 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. . Major Responsibilities:. . . Use SQL, Python, or other analytical tools to query, clean, and analyze large datasets.. Analyze labor market trends across dimensions such as workforce composition, job demand, employment patterns, and wage dynamics.. Apply advanced techniques including time series forecasting, clustering, regression analysis, and machine learning algorithms (e.g., decision trees, random forests, gradient boosting, support vector machines, k-means clustering) to identify patterns and forecast labor trends.. Build and maintain scalable data and model . pipelines. using orchestration tools like Apache Airflow, Luigi, or Sagemaker Pipelines, and model tracking tools such as MLflow.. Collaborate cross-functionally to define problem statements, gather and analyze data, integrate models into products, and translate insights into actionable recommendations for technical and non-technical audiences.. Stay informed on advancements in labor market analytics, statistical modeling, and machine learning technologies.. . Education and Experience:. . . Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Computer Science, or a related quantitative field.. 2+ years of industry experience or academic research applying statistical or machine learning approaches to real-world data problems.. Proficiency in Python, SQL, and machine learning libraries such as Scikit-learn or . PyTorch. .. Demonstrated ability to write clean, scalable code and independently prototype data solutions.. Solid understanding of machine learning techniques such as classification, regression, and time-series forecasting.. Experience with cloud platforms (e.g., AWS) and orchestration tools like Apache Airflow for managing large datasets and workflows.. Strong statistical reasoning and ability to translate complex data into strategic business insights.. Excellent interpersonal, written, and verbal communication skills, with the ability to convey technical topics to diverse audiences.. Experience working with large labor market datasets (e.g., government labor statistics, survey data, or job market intelligence platforms) (preferred).. 2+ years of experience in labor market analytics, workforce intelligence, or related domains (preferred).. Proficiency with data visualization tools such as Tableau, Power BI, or Plotly (preferred).. Familiarity with Natural Language Processing (NLP) techniques and applications (preferred).. Lightcast is a global leader in labor market insights with headquarters in Moscow (ID) with offices in the United Kingdom, Europe, and India. We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities. Lightcast is proud to be an equal opportunity workplace and is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Lightcast has always been, and always will be, committed to diversity, equity and inclusion. We seek dynamic professionals from all backgrounds to join our teams, and we encourage our employees to bring their authentic, original, and best selves to work.. .