Senior Data Scientist
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Job Description
Senior Data Scientist developing embedding-based deep-learning models for Jampp’s mobile advertising technology. Deploying real-time prediction, bidding, and optimization systems at scale.
Responsibilities:
- Design, develop and iterate deep learning models for prediction and optimization
- Develop embedding-based approaches to represent high-cardinality entities such as users, devices, creatives, publishers, advertisers, apps, campaigns and placements
- Identify opportunities to improve the performance, scalability and generalization of machine learning models using raw signals and learned representations
- Experiment with different modeling approaches, evaluate results rigorously and translate successful experiments into production solutions
- Design, code and deploy machine learning models and supporting production tools, primarily in Python
- Work with large-scale datasets and contribute to data pipelines, feature infrastructure and feedback loops required to train and continuously improve models
- Collaborate with ML Engineers, Data Engineers and Software Engineers to ensure models can be trained, served and monitored reliably in production
- Analyze model and product performance metrics to understand how algorithm changes impact bidding, campaign performance and business outcomes
- Communicate technical findings and trade-offs clearly, and collaborate with other Data Science teams to share knowledge and best practices
Requirements:
- +5 years of experience in Data Science, Machine Learning or a closely related quantitative role
- Strong academic background in Applied Mathematics, Physics, Statistics, Computer Science, Econometrics, or another quantitative field
- Strong experience with Python and the scientific/machine learning Python ecosystem
- Hands-on experience developing and evaluating machine learning models, with a solid understanding of statistical and machine learning fundamentals
- Practical experience with Deep Learning and neural network architectures
- Experience working with large-scale datasets and/or high-cardinality categorical or ID-based features
- Ability to take models from experimentation through production, working closely with engineering teams
- Strong analytical and problem-solving skills, with the ability to independently investigate ambiguous problems and turn them into actionable solutions
- Comfortable conducting daily professional communications in English (written and verbal)
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