Data Scientist Engineer

This role involves leveraging advanced machine learning models and AI-driven solutions to address complex business problems., * AI/ML Model Development: Design and train machine learning models using various algorithms, including deep learning, NLP, and computer vision.

• Databricks Orchestration: Build and optimize end-to-end AI/ML pipelines on Databricks, utilizing Unity Catalog for governance and MLflow for experiment tracking.
• Generative AI & LLMs: Implement advanced AI patterns such as Retrieval-Augmented Generation (RAG) and fine-tune pre-trained models for specific enterprise tasks.
• Python Expertise: Write production-quality, idiomatic PySpark and Python code that leverages Spark’s distributed nature.
• Collaboration: Partner with Engineering and Product teams to translate business problems into scalable analytical solutions.
• Insight Extraction: Perform exploratory data analysis (EDA) and extract meaningful insights from massive, complex datasets to drive strategic decisions.

Do you have experience in Technical Proficiency?, Do you have a Master’s degree?, * Education: MS or PhD in a quantitative field such as Computer Science, Statistics, or Math.

• Experience: 5+ years of hands-on experience in data science or AI engineering in high-growth environments., * Technical Proficiency: Expert-level Python (pandas, NumPy, scikit-learn, PySpark).
• Extensive experience with Apache Spark for large-scale data processing.
• Proficiency in SQL for data manipulation and querying in Lakehouse environments.
• AI Foundations: Strong understanding of statistics, probability, and advanced ML lifecycle management (MLOps).

Preferred Skills

• Experience with Deep Learning frameworks (TensorFlow, PyTorch).
• Familiarity with Cloud Platforms (AWS, Azure, or GCP) and their native data services.
• Databricks certifications, such as Databricks Certified Machine Learning Professional.

Pulled from the full job description

• Health insurance
• Paid time off
• Employee assistance program