Data Scientist

Apply now: Data Scientist, location is Hybrid (Tysons, VA – 3 days onsite per week). The start date is ASAP for this 2–3 month contract position.

Job Title: Data Scientist
Location-Type: Hybrid (Tysons, VA)
Start Date Is: ASAP
Duration: 2–3 Month Contract
Compensation Range: $60-65/hr on W2

The Data Scientist will design and implement NLP-driven content classification models to modernize and enhance the client's content taxonomy and categorization systems.

Day-to-Day Responsibilities:

• Partner with product, research, and content stakeholders to redesign and modernize content taxonomy

• Analyze large-scale media/content datasets to define and validate new classification schemas

• Build NLP-based, multi-level classification models from the ground up

• Develop vector-based solutions (embeddings, clustering, semantic similarity) to improve categorization

• Create research datasets and sample outputs to evaluate taxonomy effectiveness

• Write production-ready Python and SQL for model training, evaluation, and data transformation

• Develop data pipelines and integrate model outputs via APIs into existing systems

• Document taxonomy logic, modeling decisions, and trade-offs for non-technical stakeholders

Requirements:

• Must-Haves:

  • 5 years of experience as a Data Scientist or NLP-focused data professional

  • Strong hands-on experience in NLP and text classification

  • Proven experience building classification models from scratch

  • Experience with taxonomy design or hierarchical content labeling systems

  • Advanced Python (modeling, pipelines, data manipulation)

  • Strong SQL for large-scale analysis and validation

  • Experience with vectors/embeddings (semantic similarity, clustering)

  • Comfortable in greenfield environments with limited structure

  • Ability to translate ambiguous business goals into clear technical solutions

• Nice-to-Haves:

  • Experience integrating ML models via APIs into content management systems

  • Background in media, publishing, or content-driven environments

  • Experience building features that support analytics and downstream reporting