
Data Science Engineer
3 days ago
We are seeking a highly skilled Data Science Engineer with 5+ years of experience to join our client's fast-growing SaaS business. The ideal candidate will work at the intersection of data engineering, machine learning, and product development, building scalable data solutions that power business decisions and enhance product performance.
Key Responsibilities- Design, develop, and maintain data pipelines and ETL processes for large-scale data.
- Build, train, and deploy machine learning models to solve business problems and optimize SaaS product features.
- Collaborate with product, engineering, and business teams to translate requirements into data-driven solutions.
- Perform statistical analysis, predictive modeling, and A/B testing to generate insights.
- Ensure data accuracy, quality, and governance across all systems.
- Implement and optimize data storage, retrieval, and real-time processing solutions.
- Monitor model performance and continuously improve algorithms.
- Document processes, models, and best practices for reproducibility.
- 5+ years of experience as a Data Science Engineer / Machine Learning Engineer.
- Strong proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Hands-on experience with big data technologies (Spark, Hadoop, Kafka) and cloud platforms (AWS, GCP, Azure).
- Deep understanding of statistical modeling, data mining, and predictive analytics.
- Experience with data pipelines and workflow orchestration tools (Airflow, Luigi, Prefect).
- Strong problem-solving and analytical skills with the ability to work in fast-paced SaaS environments.
- Excellent communication skills to present findings to both technical and non-technical stakeholders.
- Exposure to NLP, recommendation systems, or deep learning applications.
- Prior experience in scaling SaaS platforms using AI/ML.
- Familiarity with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).
- Opportunity to work with a fast-growing SaaS company at the forefront of innovation.
- A dynamic environment where your work directly impacts product growth and customer success.
- Career growth in advanced data science, AI, and product engineering.
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