We are seeking a Data Scientist to join a team focused on developing and improving machine learning and AI-driven solutions that enhance content discovery, search relevance, metadata generation, and product capabilities. This role will work with large-scale structured and unstructured datasets, applying modern data science, NLP, search, retrieval, and machine learning techniques to solve complex business and product challenges.
The ideal candidate combines strong machine learning and statistical foundations with experience building practical AI solutions that can be deployed, measured, and continuously improved in production environments.
Responsibilities
- Develop, evaluate, and improve machine learning models and data science solutions that support product development and operational workflows.
- Design and implement NLP, search, retrieval, and content understanding solutions using modern machine learning techniques.
- Build and optimize semantic search, ranking, recommendation, and retrieval systems to improve user experiences.
- Work with large-scale structured, semi-structured, and unstructured datasets to extract insights and create scalable solutions.
- Evaluate emerging AI, machine learning, and generative AI technologies and recommend appropriate applications.
- Partner with product, engineering, analytics, and business stakeholders to identify opportunities for data-driven innovation.
- Support the full machine learning lifecycle, including experimentation, deployment, monitoring, and ongoing model optimization.
- Develop performance metrics and evaluation frameworks to measure solution effectiveness and business impact.
- Communicate technical concepts and findings to both technical and non-technical audiences.
Required Qualifications
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 3+ years of experience in Data Science, Machine Learning, Applied AI, or a related discipline.
- Strong programming skills in Python, including experience with Pandas, NumPy, and related data science libraries.
- Experience building and evaluating machine learning models, including classification, clustering, regression, ranking, or recommendation systems.
- Hands-on experience with Natural Language Processing (NLP) and modern language modeling techniques.
- Experience working with embeddings, semantic search, retrieval systems, or search relevance optimization.
- Familiarity with transformer-based models and large language model (LLM) applications.
- Experience working with large-scale structured, semi-structured, or unstructured datasets.
- Strong analytical, problem-solving, and communication skills.
- Authorization to work in the United States without sponsorship.
Preferred Qualifications
- Experience with Elasticsearch, OpenSearch, vector search, or search relevance platforms.
- Familiarity with MLOps, model deployment, and production machine learning environments.
- Experience with recommendation systems, knowledge graphs, or entity-resolution solutions.
- Exposure to multimodal AI, including text, image, or video-based machine learning applications.
- Master's degree in Data Science, Computer Science, Machine Learning, or a related field.
Desired Backgrounds
Successful candidates often come from:
- Applied AI and Machine Learning teams
- Search and Relevance Engineering organizations
- Recommendation Systems teams
- Enterprise Search and Knowledge Management platforms
- Content Intelligence and Information Retrieval environments
- Digital Media, Publishing, or Content Technology organizations
Pay: $160,000.00 - $180,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Health insurance
- Parental leave
Work Location: In person
