Data Scientist at Assembly building and automating media intelligence models. Collaborating with consultancy leadership to define analytical approaches to business challenges.
About the role
- Data Scientist providing data-driven insights and scientific solutions at ShyftLabs. Collaborating with cross-functional teams to enhance product strategies and business outcomes through machine learning.
Responsibilities
- Analyze large datasets using queries and scripts to extract meaningful insights and identify opportunities for improving complex ML and bidding systems.
- Design and execute simulations to validate hypotheses, quantify efficiency gains, and model system performance.
- Develop robust experiment designs and metric frameworks to deliver unbiased, data-backed insights for product and business decisions.
- Build, train, and deploy ML models into production environments, managing the full lifecycle including versioning, monitoring, and retraining.
- Operationalize ML models at scale, optimizing for performance, reliability, and cost efficiency in real-world production systems.
- Work closely with product, engineering, and data teams to translate business problems into analytical solutions.
Requirements
- Master’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Data Science) or equivalent experience.
- 3+ years of professional experience in data science or applied machine learning.
- Strong problem-solving and analytical skills, with the ability to turn complex product questions into actionable insights.
- Excellent communication skills, both verbal and written, with the ability to present technical results to non-technical audiences.
- Proven ability to build and maintain strong relationships with stakeholders across teams and functions.
- Deep understanding of machine learning algorithms, from classical methods (e.g., regression, random forests, k-means) to advanced techniques (e.g., gradient boosting frameworks such as XGBoost, LightGBM, CatBoost, and transformer-based architectures like BERT or Sentence Transformers).
- Proficiency in Python or R, and data manipulation tools/libraries such as Pandas and SQL.
- Hands-on experience deploying models in production and managing ML lifecycle processes (monitoring, retraining, version control).
Benefits
- Strong insurance package
- Extensive learning and development resources
Job title
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Not specified
Degree requirement
Tech skills
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