Data Scientist

Ardent Principles, Inc.•,

29d•Onsite

About The Position

We are seeking a highly capable Data Scientist with demonstrated experience in advanced natural language processing, machine learning, and analytical research to support mission‑focused initiatives. The ideal candidate brings hands‑on expertise with Python‑based NLP workflows, deep learning frameworks, and modern transformer architectures, along with the ability to clearly communicate methodological decisions and analytical findings to technical and senior‑level audiences. Ardent Principles signifies our unwavering commitment to excellence, driven by a profound passion and a strict adherence to ethical values. We believe that happy employees make for happy clients. Our mission is to act as a bridge between satisfied clients and fulfilled employees, ensuring that your job and well-being are our top priorities because your satisfaction leads to the success of our clients. With a competitive salary and industry-leading benefits, Ardent Principles offers more than just a job - we offer a career path filled with growth and opportunities. Join us and let's shape the future together!

Requirements

Active TS/SCI with Full Scope Polygraph
Demonstrated experience in advanced natural language processing, machine learning, and analytical research
Hands-on expertise with Python-based NLP workflows
Hands-on expertise with deep learning frameworks
Hands-on expertise with modern transformer architectures
Ability to clearly communicate methodological decisions and analytical findings to technical and senior-level audiences
Professional or academic experience performing NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
Professional or academic experience using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents.
Professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras.
Professional or academic experience with the HuggingFace Transformers library and hub.
Creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models.
Academic or professional experience using encoder-decoder and generative language models to perform NLP tasks.
Academic or professional experience communicating methodological choices and model results.
Professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries.
Professional or academic experience with version control systems such as Github and Jenkins.
Leveraging GPUs for accelerated computing.
Developing practical approaches for measuring performance.
Assisting in developing types of measure, the collection of data, analyzing the data, and presenting that data to senior leadership.
Conducting advanced statistical analysis on personnel, intelligence, and performance metrics.
Assisting in selection or development of appropriate methodology to conduct research.
Analyzing information and provide research findings in a manner that is easily grasped by the customer and consumers.

Nice To Haves

Writing Python scripts that pull data from web-based APIs and relational databases.
Cloud computing development and architecture
Front-end web development frameworks such as Flask.
Developing applications for semantic search.
Tuning LLMs on custom data sets and applying results to specific use cases.
Professional or academic experience and proficiency with Tableau to produce visualizations and dashboards.

Responsibilities

Performing NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
Using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents.
Using deep learning frameworks such as PyTorch, Tensorflow, or Keras.
Using the HuggingFace Transformers library and hub.
Creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models.
Using encoder-decoder and generative language models to perform NLP tasks.
Communicating methodological choices and model results.
Using SQL to include common table expressions, set operations, aggregated functions and nested subqueries.
Using version control systems such as Github and Jenkins.
Leveraging GPUs for accelerated computing.
Developing practical approaches for measuring performance.
Assisting in developing types of measure, the collection of data, analyzing the data, and presenting that data to senior leadership.
Conducting advanced statistical analysis on personnel, intelligence, and performance metrics.
Assisting in selection or development of appropriate methodology to conduct research.
Analyzing information and provide research findings in a manner that is easily grasped by the customer and consumers.