Data Scientist

NeuroHire is seeking a motivated and analytical Data Scientist to join our team. In this role, you will work with structured and unstructured datasets to discover meaningful patterns, develop predictive models, and generate data-driven insights that support business objectives and strategic decision-making. You will collaborate with technical and business teams to explore data, build machine learning models, evaluate analytical results, and help transform complex datasets into actionable solutions. This position is ideal for an early-career professional who is passionate about statistics, programming, machine learning, and solving real-world problems through data. Key Responsibilities Collect, clean, process, and analyze large datasets from multiple sources to identify patterns, trends, and meaningful insights. Perform exploratory data analysis (EDA) to understand data distributions, relationships, and potential business opportunities. Develop, train, test, and evaluate machine learning models to solve analytical and predictive problems. Apply statistical techniques and mathematical methods to interpret data and support evidence-based decisions. Write efficient code using Python and relevant data science libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib. Build predictive models, classification algorithms, regression models, and other machine learning solutions. Work with SQL databases to extract, manipulate, and analyze structured data. Create data visualizations, reports, and presentations to communicate analytical findings. Evaluate model performance using appropriate metrics and recommend improvements. Collaborate with software engineers, data analysts, and cross-functional teams to translate business requirements into analytical solutions. Assist in developing and improving data processing and machine learning workflows. Maintain documentation of datasets, analytical methodologies, experiments, and model results. Stay updated with emerging data science techniques, machine learning technologies, and industry best practices.