Job Title

Company DescriptionRazonica helps retail and e-commerce companies grow faster. Our product/ services help retail and e-commerce companies find growth opportunities without needing to depend on their ability to pay for experience or resort to trial and error. Both can be expensive.We are replacing this trial and error with deep analytics and predictive modeling so that the companies can be built faster.Role DescriptionThis is a full-time remote role for a Data Science & Engineering Intern. The intern will assist in data analysis, data science projects, and the application of statistical methods. The intern will conduct data analytics tasks including data cleaning, data preparation, and exploratory data analysis. Additionally, the intern will work on building, testing, and deploying machine learning models, and generate insights from data to support business decisions.What You’ll Work OnAs a Data Science & Engineering Intern, you'll work on high-impact, real-world projects. Your responsibilities will include:Building data engineering pipelines to enable efficient data aggregationPerforming descriptive and exploratory data analysisCollaborating with the team to build and refine ML hypothesesScraping, cleaning, and preprocessing diverse data sourcesDesigning and training ML models (clustering, time series, predictive modeling, etc.)Translating model results into actionable insightsDocumenting your work clearly for feedback and reproducibilityYou’ll be assigned 4 projects per month, and you’ll have the opportunity to work independently with regular team check-ins and mentorship.What We’re Looking ForYou're a great fit if you have a curious mind, a hands-on approach, and a strong foundation in:Python (pandas, NumPy, scikit-learn, etc.)Data engineering and pipeline designData cleaning and preprocessingML modeling (supervised and unsupervised techniques)Data visualization (Matplotlib, Seaborn, Plotly, or similar)Bonus points if you’ve worked on real-world projects!Internship DetailsTime Commitment: 12–18 hours/weekDuration: 6 monthsCompensation: Project-based payouts depending on performanceLetters of Recommendation from the company or senior data scientists based on performance