Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee applied AI initiatives from inception to realization, encompassing prototyping, validation, and deployment of effective ML and GenAI solutions.

• Serve as an internal AI advisor across product, engineering, security, and research departments.

• Spearhead the research, development, and implementation of models aimed at detecting malicious behavior, anomalies, and fraud.

• Create experiments and evaluation frameworks to assess model reliability, accuracy, and business impact.

• Connect research with production by converting insights into scalable APIs, tools, or workflows.

• Investigate LLMs, embeddings, retrieval-augmented generation, and agentic workflows.

• Convey technical concepts, trade-offs, and suggestions through presentations, documentation, and collaboration.

• Mentor colleagues to enhance organizational AI knowledge and capabilities.

• Collaborate with data governance teams to ensure data privacy and ethical compliance.

⛳️ Requirements

• A minimum of 5 years of hands-on experience in applied data science, machine learning, AI engineering, or AI research.

• A degree in Computer Science or a related technical field is highly preferred.

• Proficient in Python programming.

• Practical experience with Databricks, LLM APIs, and scikit-learn.

• Proven track record of building and deploying ML or GenAI applications from prototype to functional workflows.

• Extensive familiarity with OpenAI, Anthropic/Claude, Hugging Face, and open-weight models.

• Capability to design LLM applications utilizing prompting, context management, structured outputs, retrieval, and tool usage.

• Experience with agentic or multi-step AI workflows using frameworks such as LangGraph, LangChain, Semantic Kernel, or similar.

• Proficient in defining quality metrics, evaluation datasets, reliability assessments, and data-driven decision-making.

• Comfortable working with large, complex, structured, and unstructured data.

• Skilled in Git, testing, code reviews, and collaborative software development practices.

• Excellent written and verbal communication abilities.

• Preferred: strong MLOps experience, familiarity with MLflow or similar tools, CI/CD, serving, production monitoring, observability, tracing, incident response, drift detection, managed ML platforms, MCP, LLM guardrails, AI-assisted development tools, cybersecurity or fraud detection, PySpark, production data pipelines, and SaaS experience.

🏝️ Benefits

• Parental leave.

• Participation in diversity and inclusion working groups.

• Flexible working arrangements.

• Paid Volunteer Time Off (VTO).

• Equal-opportunity employer.

• Accommodations for disability and special needs.