Iris Software is looking for a Data Science Lead to join our team. You will lead the design, implementation, and maintenance of data science pipelines from data ingestion to model deployment. This role is central to our mission of building impactful data-driven solutions within our award-winning culture that values talent, ambitions, and a voice that matters.
What You'll Do
- 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.
What We're Looking For
- Bachelor’s or Master’s 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 MLflow, SageMaker, 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, BigQuery).
- 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.
Nice to Have
- Experience with containerization and orchestration (Docker, Kubernetes).
- Experience working in Agile or cross-functional teams.
- Familiarity with streaming data platforms (Kafka, Spark Streaming, Flink).
Technical Stack
- Languages: Python, SQL, Java, Scala, C++
- ML Libraries & Tools: Scikit-learn, XGBoost, TensorFlow, PyTorch, MLflow, AWS SageMaker, Vertex AI
- Data Processing: Spark, Pandas, Kafka, Spark Streaming, Flink
- Cloud & Infrastructure: AWS, Docker, Kubernetes
- Data Storage: SQL, NoSQL, Delta Lake, BigQuery, Apache Hudi
- AWS Services: AWS Glue, AWS EMR, Amazon Data Pipeline, AWS Redshift, Amazon IAM, AWS Secrets Manager, AWS KMS, AWS Cognito
Iris Software is an equal opportunity employer.
