Junior Data Scientist
Summary
Junior Data Scientist at a consulting firm supporting health research on critical illness and infectious diseases. Day to day: statistical analysis and data manipulation in R/Python, building NLP/LLM pipelines to extract structured info from clinical text, and SQL work against research databases.
Overview
Black Canyon Consulting (BCC) is searching for a Junior Data Scientist. This position supports research data analysis, dissemination, and scientific programming activities related to critical illness, infectious diseases, and related conditions of high national priority..
Job Description
The Data Engineer will design, implement, maintain, and optimize data pipelines, APIs, data transformation workflows, and supporting infrastructure. This position will work with databases, data lakes, data warehouses, feature stores, and other data platforms to ensure information can be efficiently ingested, transformed, accessed, and used by analytical and AI-enabled systems.
The Data Engineer will also develop and maintain ETL/ELT processes, feature engineering workflows, and service layers that expose data or model endpoints to downstream systems and applications.
Required Skills
- Expertise in R or Python for statistical analysis and data manipulation
- Experience using NLP techniques including named entity recognition, text classification, or information extraction to process data
- Experience with LLM prompt engineering, retrieval-augmented generation, and LLM fine-tuning to extract structured information from unstructured data
- Working knowledge of standard machine learning methods relevant to health data
- Ability to critically evaluate AI/ML methods for appropriateness, bias, and validity in a clinical research context
- Strong oral and written communication skills, including the ability to translate technical findings for clinical/non-technical collaborators
- Ability to work collaboratively with physician and clinical subject matter experts
- Detail-oriented, with strong data quality assurance habits
- Strong analytical, organizational, and time-management abilities
- Working knowledge of MS Office Suite
- Working knowledge of SQL and relational database management systems (DBMS)
Preferred Skills
- Experience with common NLP/ML libraries
- Familiarity with clinical NLP tools or frameworks
- Experience with vector databases or embedding-based retrieval for text/document search
- Data visualization experience
- Version control and documentation experience
- Familiarity with administrative claims and/or EHR data
- Prior experience in an academic, clinical, or biomedical research setting
- Understanding of data privacy and regulatory requirements relevant to health data
Benefits and Salary
We attract the best people in the business with our competitive benefits package that includes medical, dental and vision coverage, 401k plan with employer contribution, paid holidays, vacation, and tuition reimbursement.
If you enjoy being a part of a high performing, professional service and technology focused organization, please apply today!
Skills
As published by greenhouse · 5 questions · 3 written answers
Basics
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter, Location
Short answers (1)
- What are your salary requirements?
Pick from a list (1)
- Will you now, or in the future, require visa sponsorship? This includes if you are on a STEM OPT, J-1, F-1 visa currently.
Written answers (3)
- Describe a project where you used Python or R to analyze clinical, biomedical, or other complex health-related data. What was the research question, what data did you work with, and what analytical approach did you use?
- Tell us about a project where you used NLP, large language models, or retrieval-augmented generation to extract or structure information from unstructured text. What techniques or tools did you use, and how did you evaluate the accuracy and reliability of the results?
- Describe a time you worked with clinicians, scientists, or other non-technical subject matter experts on a research or data-analysis project. How did you translate their research needs into an analytical approach, and how did you communicate your findings back to them?