Junior Predictive Analytics Engineer
Position filledWhat You’ll Do
- Craft, test, and deploy predictive models that power revenue forecasts, risk scores, and personalized recommendations.
- Write clear, reusable Python 3.x code - NumPy, pandas, scikit-learn, PyTorch - for data pipelines and model training.
- Explore large structured and unstructured data sets; cleanse, aggregate, and feature-engineer with statistical rigor.
- Evaluate accuracy using cross-validation, A/B tests, ROC-AUC, and lift charts; iterate until performance targets are met.
- Debug model drift and data quality issues, proposing swift, testable fixes.
- Document architecture, assumptions, and experiment results to support regulatory and stakeholder reviews.
- Collaborate with product, design, and DevOps to push models into scalable microservices or batch jobs.
- Monitor live forecasts, surface anomaly alerts, and suggest optimization tactics that sharpen decision-making.
What You Bring
- Bachelor’s degree (or higher) in Computer Science, Statistics, Applied Mathematics, or related STEM field.
- 0-2 years’ professional experience - or substantial internship/project work - in predictive analytics or machine learning.
- Solid Python proficiency; comfort with Git, Jupyter, and UNIX command line.
- Working knowledge of probability, linear regression, classification, and time-series forecasting.
- Familiarity with SQL, bonus points for BigQuery, Snowflake, or Spark.
- Skillful verbal and written communication - you explain complex patterns in plain English.
- Adaptable mindset, eagerness to hunt down edge-cases, and drive to learn fast.