 
						Data Science Engineer
4 weeks 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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