Description:
At Company's, our data science team tackles diverse research challenges in digital experience optimization, crafting cutting-edge solutions to help businesses grow. As a Senior Data Scientist, you will play a pivotal role, directly engaging with senior leadership while fostering a culture of learning through experimentation. You'll collaborate with teams across product development, engineering, and customer success to create impactful solutions, blending business insight with rigorous research.
The core responsibilities for the job include the following:
Recommendation Systems:
- Content, product, and experience recommendations.
- Hybrid recommenders combining behavior, context, and semantics.
User Profiling and Auto-Segmentation:
- Automatic user profiling based on behavioral signals.
- Affinity detection and interest clustering that generalizes across diverse industries.
- ML-driven dynamic user segmentation.
Attractiveness and Ranking Models:
- Ranking experiences/items based on likelihood of engagement or conversion.
- Moving beyond relevance to attractiveness and intent-aware scoring.
Experimentation and Impact Measurement:
- Designing models that are testable via A/B experiments.
- Measuring incremental impact on conversion, engagement, and retention.
Requirements:
- 4 to 8 years of industry experience in data science / applied ML.
- Strong foundations in machine learning (classification, clustering, ranking, and recommendations), statistics, and experimentation.
- Proficiency in Python and common ML libraries.
- Strong SQL skills and experience working with large datasets.
- Ability to own problems independently and make good trade-offs.
- Appreciation for clean, robust, and maintainable solutions.
- Experience with: recommendation systems (collaborative, content-based, and hybrid); user segmentation or personalization systems; and clickstream / event-based data.
- Exposure to building real-time search systems, NLP, embeddings, or representation learning.
- Prior work in B2C products, especially at scale.
- Familiarity with A/B testing frameworks or experimentation platforms.
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