Senior/Principal Applied Data Scientist

Remote

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, SaaS, BiotechnologyIndustries

Requirements

Candidates should have a background in data science, agentic frameworks, machine learning, and engineering, with strong programming skills in Python. Deep experience extracting structured data from unstructured PDFs using frameworks like DSPy, Pydantic, Trustcall, LangGraph, LangChain, LlamaIndex, and Docling is required, along with a deep understanding of LLM models. Experience working with both technical and non-technical stakeholders, excellent communication and collaboration skills, and a strong grasp of the full MLOps lifecycle, including data engineering, training/evaluation, serving, and monitoring, are also necessary. Proficiency in creating Docker containers is required, with experience in cloud platforms (AWS, GCP, Azure) and familiarity with Bedrock and Anthropic models being advantageous.

Responsibilities

The Senior/Principal Applied Data Scientist will build and design intelligent agentic workflows, solve complex data science problems in document classification and structured data extraction, and write code to extract structured information from unstructured patient records. Responsibilities include leveraging deep technical expertise to support customers and troubleshoot complex issues, developing a customer knowledge base to reduce onboarding time, and working with the product team to prioritize the roadmap based on customer feedback. The role also involves communicating findings to stakeholders and ensuring privacy and compliance standards (HIPAA, PHI/PII) are upheld throughout the ML lifecycle.

Skills

Data Science

Agentic Workflows

Document Extraction

Customer Success

Engineering

Solutions Engineering

Document Classification

Structured Data Extraction

Python

Data Analysis

Machine Learning

Problem Solving

Communication

Cape

Subscription-based mobile network prioritizing privacy

About Cape

Cape provides a mobile network service that focuses on delivering secure and private wireless coverage. The service works on a subscription model, where customers pay a regular fee to access Cape's network, which is designed to keep their personal information safe. Cape uses advanced technologies to ensure that users' names, numbers, and locations are protected from hackers, allowing them to communicate without fear of their data being compromised. What sets Cape apart from other mobile network providers is its strong commitment to privacy; it minimizes data collection and never sells or misuses customer information. The goal of Cape is to meet the growing demand for secure mobile communications, making it a leader in the privacy-first movement within the telecommunications industry.

Chesapeake, VirginiaHeadquarters

1998Year Founded

$59.3MTotal Funding

SERIES_BCompany Stage

Consumer Software, CybersecurityIndustries

51-200Employees

Benefits

Health Insurance

Unlimited Paid Time Off

401(k) Company Match

Risks

Increased competition from established privacy-focused telecom players like Silent Circle.

Quantum computing advancements could threaten current encryption methods used by Cape.

Government regulations on data retention may conflict with Cape's privacy-first model.

Differentiation

Cape offers privacy-first mobile services, ensuring minimal data collection and no data selling.

The company uses advanced technology to make user data untraceable by hackers.

Cape's subscription model provides secure, anonymous wireless coverage for privacy-conscious individuals.

Upsides

Growing demand for privacy-focused mobile services boosts Cape's market potential.

Partnership with IT&E Guam enhances Cape's market reach and credibility.

Recent $61 million funding round indicates strong venture capital interest in privacy-first tech.

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