About the Role RippleHire is seeking a talented Data Scientist with strong foundational skills and hands-on experience in predictive modeling to join our growing team. This is an excellent opportunity for a mid-level professional looking to make significant impact while continuing to grow their expertise. Key Responsibilities • Build and implement predictive models for business problems such as customer segmentation, churn prediction, and demand forecasting • Perform data analysis and create insights from structured and unstructured data • Clean, preprocess, and perform feature engineering on datasets • Evaluate model performance and iterate to improve accuracy • Document models and analysis for technical and business stakeholders Collaboration & Delivery • Work with business teams to understand requirements and translate them into analytical solutions • Create visualizations and presentations to communicate findings • Participate in code reviews and knowledge sharing sessions • Support deployment of models with the engineering team Required Qualifications Experience • 3-5 years of experience in data science, analytics, or related field • At least 2 years of hands-on experience building predictive models • Experience working with real business datasets and delivering analytical solutions Technical Skills - Must Have • Strong proficiency in Python and its data science libraries (pandas, numpy, scikit-learn) • Good understanding of machine learning algorithms (regression, classification, clustering) • Experience with SQL for data extraction and manipulation • Basic statistics knowledge (hypothesis testing, probability distributions) • Experience with data visualization (matplotlib, seaborn, or similar) • Familiarity with Jupyter notebooks and Git Technical Skills - Good to Have • Experience with any cloud platform (AWS, GCP (Preferred), or Azure) • Basic knowledge of deep learning frameworks (TensorFlow or PyTorch) • Exposure to LLMs and prompt engineering • Experience with any BI tool (Tableau, Power BI) • Knowledge of big data tools (Spark basics) • Knowledge of Vector Database Preferred Qualifications • Bachelor's or Master's degree in Engineering, Computer Science, Statistics, Mathematics, or related field • Kaggle participation or personal ML projects on GitHub • Experience with A/B testing • Basic understanding of MLOps concepts • Any experience with NLP or time series analysis What Makes You a Good Fit • You have successfully built and deployed at least 2-3 predictive models • You're comfortable working with messy, real-world data • You can explain technical concepts to non-technical stakeholders • You're eager to learn new technologies, especially in the AI/LLM space • You're detail-oriented and write clean, documented code Growth Opportunities • Clear path to Senior Data Scientist role • Exposure to LLM projects and cutting-edge AI technologies • Mentorship from senior team members • Cross-functional project opportunities