The ideal candidate has hands-on experience with data wrangling, exploratory data analysis, statistical modeling, machine learning algorithms, and data visualization, and can work effectively with large and complex datasets in an enterprise IT
• Apply the scientific method to frame problems, test hypotheses, and validate results •
Perform data wrangling, cleansing, and preprocessing on structured and unstructured datasets • Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies • Build, evaluate, and deploy statistical and machine learning models • Apply a variety of machine learning algorithms (e.g., regression, classification, clustering, ensemble methods) • Work with large-scale datasets and big data processing frameworks • Create data visualizations and dashboards to communicate insights effectively • Collaborate with cross-functional teams including IT, data engineering, analytics, and business stakeholders • Translate complex analytical findings into clear, actionable recommendations • Document methodologies, models, assumptions, and results Required
• 5–10 years of experience in data science, analytics, or a related role •
Strong proficiency in statistics and probability • Proficiency in at least one programming language: • Python or • R • Hands-on experience with data wrangling, analysis, and exploration •
Familiarity with a wide range of machine learning algorithms • Experience creating data visualizations using industry-standard tools or libraries •