Data Scientist | Scrabble
Job Description
Data Scientist - AI and Machine Learning
Company Overview
No details provided.
Job Summary
The Data Scientist role is a pivotal position within the Data Science/Engineering team, focusing on utilizing advanced machine learning techniques and large language models to innovate and optimize our marketing platform. The successful candidate will take ownership of projects, collaborate with top-tier talent, and contribute to building solutions at scale for a diverse user base.
Responsibilities
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Unified AI Strategy & Technical Leadership
- Design and own the end-to-end technical vision for the next-generation marketing platform, integrating recommender systems and large language models (LLMs).
- Lead research, design, and implementation of innovative models that combine predictive strategies with generative capabilities.
- Establish best practices across the entire modeling stack, from classical ML fundamentals to MLOps.
- Act as the primary technical mentor for data scientists, guiding them on feature engineering and fine-tuning LLMs.
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Recommender System Innovation & Optimization
- Architect, build, and deploy large-scale recommender systems using various techniques (e.g., collaborative filtering, matrix factorization).
- Address recommendation challenges, including the cold-start problem and real-time personalization.
- Implement rigorous offline and online evaluation frameworks to monitor and enhance recommendation quality.
- Utilize classical machine learning models (e.g., XGBoost, Logistic Regression) to predict user behavior and inform the recommendation engine.
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Generative AI & LLM Integration
- Develop LLM-powered features, including campaign optimizers and natural language interfaces.
- Adapt pre-trained LLMs on proprietary data for improved relevance and factuality.
- Design Retrieval-Augmented Generation (RAG) pipelines for reasoning across product catalogs.
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Cross-Functional Influence & Execution
- Collaborate with Product, Engineering, and Design leaders to create a detailed technical roadmap based on business objectives.
- Effectively communicate complex ideas to both technical and non-technical audiences.
- Manage projects from ideation to deployment, ensuring models are accurate, scalable, and efficient.
Qualifications
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Education:
- Bachelor’s, Master’s degree, or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
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Experience:
- 7+ years of hands-on experience building and deploying machine learning models in a business environment.
- Proven track record of leading complex data science projects with significant business impact.
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Technical Skills:
- Expert-level proficiency in Python and its data science libraries (e.g., pandas, NumPy, scikit-learn, XGBoost, Spark).
- Advanced proficiency in SQL for querying large and complex datasets.
- 2+ years of hands-on experience with Large Language Models (e.g., fine-tuning, prompt engineering, RAG).
Preferred Skills
- Experience with cloud-based ML platforms/ML Ops (e.g., AWS SageMaker, MLflow) and generative AI services.
- Practical experience with vector databases.
- Familiarity with frameworks like LangChain or LlamaIndex for LLM applications.
- Understanding of operational considerations for LLMs, including cost management and responsible AI principles.
Experience
- A minimum of 7 years of relevant experience in machine learning and data science roles.
Environment
No details provided regarding work setting or location.
Salary
Salary information not provided.
Growth Opportunities
No specific growth opportunities mentioned.
Benefits
No benefits information provided.