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
- 5 -8 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
