Senior Data Scientist

ETHOS - Talent & Advisory; Maryland; On-site; USD 180,000 - 260,000; Full time

Job summary

ETHOS - Talent & Advisory in Maryland is seeking a hands-on senior data scientist at the intersection of NLP, LLMs, and real-world data problems. You’ll design pipelines, shape analytics, and translate findings for technical and executive audiences.

You will develop and optimize NLP/LLM models, deploy cloud-native solutions on AWS, work with SQL-based data, and communicate insights to cross-functional teams.

Qualifications

• 10+ years of experience in IT/Data Science roles.
• Strong NLP expertise with modern frameworks and libraries.
• Proficiency in Python data stack: Pandas, NumPy, Matplotlib.
• Experience deploying ML/LLM solutions in cloud environments (AWS).
• Ability to translate analytic results for technical and executive audiences.

Responsibilities

• Develop, train, and optimize NLP/LLM models; build Python-based pipelines for scalable deployment.
• Design and deploy ML/Generative AI solutions in cloud-native environments (AWS).
• Analyze complex transactional and trend data using SQL, Pandas, and related tools.
• Identify analytic problems, evaluate solutions, and deliver clear recommendations.
• Collaborate with data collectors and analysts to address complex monitoring challenges.
• Build, test, and evaluate supervised and unsupervised models using advanced statistical methods.
• Process large volumes of real-world data from diverse sources (DB2, Oracle, SQL Server, Hadoop, flat files).
• Communicate findings and analytic insights to cross-functional teams and executive leadership.

Skills

NLP

LangChain

spaCy

NLTK

Python

Pandas

NumPy

Matplotlib

ML frameworks

DevOps

MLOps

LLMOps

TensorFlow

PyTorch

scikit-learn

Apache Spark

Airflow

SQL

PostgreSQL

MySQL

SQL Server

Education

Bachelor's degree in Statistics / Applied Mathematics / Computer Science / Information Science (or equivalent)

Tools

DB2

Oracle

SQL Server

Hadoop

Apache Spark

Airflow

LaTeX

HTML

Job description

This is a hands-on senior role for a data scientist who lives at the intersection of NLP, LLMs, and real-world data problems. You won’t just build models you’ll design pipelines, shape the analytic approach, and translate complex findings for technical and executive audiences alike. If you’re excited about applying Generative AI to meaningful, large-scale challenges, this is worth a look.

WHAT YOU’LL DO

• Develop, train, and optimize NLP and LLM models; build Python-based pipelines for scalable deployment
• Design and deploy ML and Generative AI solutions in cloud-native environments (AWS)
• Analyze complex transactional and trend data using SQL, Pandas, and related tools
• Identify analytic problems, evaluate solution options, and deliver clear recommendations
• Collaborate with data collectors and analysts to close gaps on complex monitoring challenges
• Build, test, and evaluate supervised and unsupervised models using advanced statistical methods
• Clean and process large volumes of real-world data from diverse sources (DB2, Oracle, SQL Server, Hadoop, flat files)
• Communicate findings and analytic insights to cross-functional teams and executive leadership

WHAT YOU BRING

• 10+ years of experience in the IT industry; BS in Statistics, Applied Mathematics, Computer Science, or Information Science (or equivalent)
• Deep expertise in NLP — spaCy, NLTK, LangChain, and related frameworks
• Strong Python fluency: Pandas, NumPy, Matplotlib, and standard ML frameworks
• Experience with ML model deployment and operations — DevOps, MLOps, LLMOps
• Hands-on experience with TensorFlow, PyTorch, and/or scikit-learn
• Experience with scalable data engineering tools such as Apache Spark and orchestration frameworks like Airflow
• Solid database skills across PostgreSQL, MySQL, SQL Server, or similar
• Proven self-starter — comfortable operating independently and driving work forward without close supervision

STRONG PLUS

• Prior experience on federal or state government IT projects
• Experience with GPU programming (CUDA) or distributed processing via Hadoop (Spark, Impala, Hive)
• NLP applied to anomaly detection
• Experience with semantic search frameworks
• Familiarity with Mathematica or markup languages such as LaTeX or HTML
• Background in analytical research environments