Software Data Scientist
1 month ago
Responsibilities :
- Design, develop, and deploy production-grade machine learning models for various tasks, with a strong focus on recommender systems.
- Conduct exploratory data analysis to understand data characteristics, identify patterns, and extract meaningful insights.
- Create and engineer relevant features to enhance model performance and address data challenges.
- Train and evaluate machine learning models using appropriate techniques and metrics.
- Leverage MLOps frameworks to track models, automate deployments, and ensure smooth model serving in production.
- Continuously monitor and analyze model performance to identify and address data drift and potential biases.
- Work closely with data scientists, software engineers, and product teams to understand business needs and translate them into actionable insights.
- Effectively communicate complex technical concepts to a wide range of audiences, including non-technical :
- Strong proficiency in Python programming
- Solid understanding of machine learning algorithms and techniques
- Experience with distributed computing frameworks like Snowpark or PySpark
- Familiarity with MLOps tools and practices
- Knowledge of software engineering best practices (e.g., version control, CI/CD)
- Demonstrated experience in developing and deploying machine learning models in production environments
- Experience with recommender systems is a significant plus
- Familiarity with working with large and imbalanced datasets
- Strong problem-solving and analytical skills
- Ability to work collaboratively in cross-functional teams
- Excellent communication and interpersonal skills
- Passion for machine learning and a continuous drive to learn
(ref:hirist.tech)-
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