Über
Responsibilities
Processing, cleansing, and verifying the integrity of data used for analysis.
Doing ad‑hoc analysis and presenting results in a clear manner.
Experience with feature synthesis and selection techniques to build models.
Solid understanding of regression and classification algorithm frameworks.
Apply machine learning techniques at scale on massive data sets.
Work with large language models (LLMs) for content summarization, recommendation, and personalization; apply RAG (Retrieval‑Augmented Generation) pipelines for knowledge retrieval.
Experiment with agentic AI frameworks to enhance personalization and automation.
Prior work with model evaluation benchmarks and large‑scale LLM testing frameworks.
Experience with prompt fine‑tuning techniques and LLM optimization (pre‑training, post‑training, etc.).
Collaborate with cross‑functional agile teams of software engineers, domain experts, and others to build new product features for multiple business units.
Collaborate with data scientists across a variety of businesses to prioritize and promote our machine learning efforts.
Skills and Qualifications
2‑4 years of data science experience with expertise in predictive analytics.
B.S., M.S., or Ph.D. in Data Science, Computer Science, Software Engineering, Information Science, Mathematics, Statistics, Electrical Engineering, Physics, or a related field; or equivalent experience.
Strong understanding of transformer‑based architectures, embeddings, and tokenization techniques.
Proficiency with LLM frameworks and APIs such as LangChain, Hugging Face Transformers, OpenAI, Google Vertex AI (Gemini), or Anthropic Claude, coupled with expertise in evaluation and performance benchmarking.
Demonstrated ability to implement prompt engineering, fine‑tuning, and evaluation for LLMs.
Strong understanding of personalization and recommendation algorithms, including collaborative filtering (CF), content‑based filtering, hybrid recommenders, sequence‑based or session‑based models, and graph‑based models.
Proficiency in using query languages such as SQL.
Experience with common data science toolkits such as R, scikit‑learn, NumPy, and TensorFlow.
This role is 5 days a week onsite at Internet Brands' headquarters in El Segundo, CA.
Compensation We consider a wide range of factors when determining compensation, including your background and experience. Compensation for this role is expected to range from $100‑120k and will depend on your skills, qualifications, and experience.
Benefits We offer a comprehensive benefits package designed to support the health and well‑being of you and your family. Benefits include health insurance options such as medical, dental, and vision coverage; flexible spending accounts (FSA) for medical and dependent care; short‑term and long‑term disability insurance; life and AD&D insurance; a 401(k) retirement savings plan with a company match; paid time off (PTO); paid holidays; commuter benefits; Access to our Employee Assistance Program (EAP) and well‑being coaching services; and voluntary benefits such as home, auto and pet insurance, and discounted legal and financial services.
EEO Statement Internet Brands is an equal opportunity employer, and we welcome applicants from all backgrounds. We comply with all applicable laws and regulations, including the City of Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO).
Contact Information Notice to California residents: you can find information about our privacy practices at https://www.internetbrands.com/work-with-us/cpra.
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Sprachkenntnisse
- English
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