Job Description

Role description

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