Data Scientist

2 days ago

Base Salary

$90k - $150k/yr

Responsibilities

Design and implement pipelines for AI model metadata, training-data lineage, and model performance metrics.
Build Databricks and Apache Spark infrastructure for large-scale distributed ML dataset processing.
Develop MCP servers and enable AI data distribution through MCP.
Create feature engineering, data preprocessing, model monitoring, drift detection, and performance-tracking workflows.
Implement model versioning, experiment tracking, and model registry integrations using MLflow or similar tools.
Automate AI agent discovery, classification, and enterprise inventory management.
Design knowledge graph structures for AI model relationships, dependencies, and data lineage.
Develop AI training-data quality and validation frameworks.
Collaborate with data scientists on data access patterns and feature store implementations.
Implement security and compliance controls for sensitive AI training data and model artifacts.
Document AI data architectures, schemas, and integration patterns.

At least 5 years of hands-on data engineering experience, including at least 2 years focused on AI/ML workloads.
Expert proficiency in Python and experience with PyTorch, TensorFlow, or scikit-learn.
Strong experience with Databricks, Apache Spark, and distributed computing for ML workflows.
Understanding of the machine learning lifecycle, including training, deployment, and monitoring.
Experience with feature engineering, data preprocessing, and ML data pipelines.
Knowledge of vector databases, embeddings, and similarity search for AI applications.
Proficiency in SQL for structured and unstructured data management.
Understanding of data governance, model governance, and AI ethics principles.
Bachelor’s or master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
Preferred experience with generative AI, RAG, fine-tuning, LangChain, HuggingFace, Azure ML, AWS SageMaker, Google Vertex AI, Neo4j, Amazon Neptune, model explainability, interpretability, and A/B testing.
Databricks, AWS, Azure, or GCP AI/ML certifications and open-source ML contributions or publications are preferred.

Health care coverage and wellness benefits.
Generous flexible time off.
Continuous learning resources and professional development support.
Retirement planning, continuing education support, company-matched student loan contributions, and financial wellness programs.
Family-focused benefits, retail discounts, and referral incentive awards.
The role is based in New York City and requires onsite work two days per week.
A mandatory in-person technical evaluation is part of the hiring process.