Data Scientist
Role details
Job location
Tech stack
Job description
Analyze structured and unstructured data to identify trends, patterns, and insights Develop, train, and deploy machine learning models Perform data cleaning, preprocessing, and feature engineering Build predictive and prescriptive models to support business objectives Collaborate with cross-functional teams to define data-driven solutions Visualize data and present findings to stakeholders Evaluate model performance and continuously optimize algorithms Work with large datasets using tools such as SQL, Python, or R Maintain documentation for models, datasets, and processes Stay updated on emerging trends in data science and AI
Requirements
We are seeking a talented and analytical Data Scientist to turn data into actionable insights that drive business decisions. The ideal candidate will have a strong foundation in statistics, machine learning, and data analysis, with the ability to work across large datasets to uncover trends and build predictive models. This role requires both technical expertise and business acumen in a fully remote environment., Must be currently residing in the United States Valid U.S. work authorization (citizen, permanent resident, or authorized work permit holder) Proven experience as a Data Scientist or similar role Strong proficiency in Python or R Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) Solid understanding of statistics, probability, and data modeling Experience with SQL and data manipulation Strong analytical and problem-solving skills Excellent communication and presentation abilities Preferred Qualifications Degree in Data Science, Computer Science, Statistics, or a related field Experience with big data technologies (e.g., Spark, Hadoop) Familiarity with cloud platforms (AWS, Azure, or Google Cloud) Experience with data visualization tools (Tableau, Power BI) Knowledge of MLOps practices and model deployment Work Environment Fully remote role with flexible scheduling options Must be available to work within U.S. business hours Collaboration with distributed teams and stakeholders
