Data Scientist

2 days ago

Base Salary

$90k - $150k/yr

Responsibilities

Design and implement pipelines for AI model metadata, training-data lineage, training datasets, and model performance metrics.
Build Databricks and Spark infrastructure for large-scale distributed ML data processing.
Develop MCP servers and enable AI data distribution through MCP.
Create feature engineering, data preprocessing, model monitoring, drift detection, and real-time performance pipelines.
Implement model versioning, experiment tracking, and model registry integrations using MLflow or similar tools.
Automate AI agent discovery, classification, and enterprise inventory management workflows.
Design and maintain knowledge graphs representing AI model relationships, dependencies, and data lineage.
Develop AI-specific data quality frameworks for training and validation datasets.
Collaborate with data scientists, ML engineers, and architects on data access patterns and feature stores.
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 Python proficiency and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
Strong Databricks, Apache Spark, and distributed-computing experience for ML workflows.
Deep understanding of machine learning training, deployment, monitoring, and lifecycle processes.
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 applications, RAG, fine-tuning, LangChain, HuggingFace, Azure ML, AWS SageMaker, Google Vertex AI, Neo4j, or Amazon Neptune.
Preferred knowledge of AI model explainability, interpretability, ML A/B testing, and Databricks, AWS, Azure, or GCP AI/ML certifications.
Publications or contributions to open-source ML projects are preferred.

Health care coverage and wellness benefits.
Generous flexible paid downtime.
Continuous learning and career-development resources.
Competitive pay, retirement planning, continuing education, company-matched student loan contributions, and financial wellness programs.
Family-focused benefits and perks.
Retail discounts and referral incentive awards.
NYC work arrangement requiring two days per week onsite.
Mandatory in-person technical evaluation as part of the hiring process.

Apache SparkDatabricksMLflowNeo4jPython PyTorchscikit-learnSQLTensorFlow