Data Science - Senior Engineer @ Iris Software

We are seeking a Data Science Engineer to design, build, and optimize scalable data and machine learning systems. This role requires strong software engineering skills, a deep understanding of data science workflows, and the ability to work cross-functionally to translate business problems into production-level data solutions.

Key Responsibilities:

• Design, implement, and maintain data science pipelines from data ingestion to model deployment.
• Collaborate with data scientists to operationalize ML models and algorithms in production environments.
• Develop robust APIs and services for ML model inference and integration.
• Build and optimize large-scale data processing systems using Spark, Pandas, or similar tools.
• Ensure data quality and pipeline reliability through rigorous testing, validation, and monitoring.
• Work with cloud infrastructure (AWS) for scalable ML deployment.
• Manage model versioning, feature engineering workflows, and experiment tracking.
• Optimize performance of models and pipelines for latency, cost, and throughput.

Required Qualifications:

• Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years of experience in a data science, ML engineering, or software engineering role.
• Proficiency in Python (preferred) and SQL; knowledge of Java, Scala, or C++ is a plus.
• Experience with data science libraries like Scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Familiarity with ML deployment tools such as ML flow, Sage Maker, or Vertex AI.
• Solid understanding of data structures, algorithms, and software engineering best practices.
• Experience working with databases (SQL, NoSQL) and data lakes (e.g., Delta Lake, Big Query).

Preferred Qualifications:

• Experience with containerization and orchestration (Docker, Kubernetes).
• Experience working in Agile or cross-functional teams.
• Familiarity with streaming data platforms (Kafka, Spark Streaming, Flink).

Soft Skills:

• Strong communication skills to bridge technical and business teams.
• Excellent problem-solving and analytical thinking.
• Self-motivated and capable of working independently or within a team.
• Passion for data and a curiosity-driven mindset.