Data Science

Job Description

Why Join Us
Are you inspired to grow your career at one ofIndia's Top 25 Best Workplaces in IT industryDo you want to do the best work of your life at one of thefastest growing IT services companies Do you aspire to thrive in an award-winning work culture thatvalues your talent and career aspirations It'shappening right hereat Iris Software.

About Iris Software
At Iris Software, our vision is to be our client's most trusted technology partner, and the first choice for the industry's top professionals to realize their full potential. With over 4,300 associates across India, U.S.A, and Canada, we help our enterprise clients thrive with technology-enabled transformation across financial services, healthcare, transportation & logistics, and professional services.

Our work covers complex, mission-critical applications with the latest technologies, such as high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation.

Working at Iris
Be valued, be inspired, be your best.
At Iris Software, we invest in and create a culture where colleagues feel valued, can explore their potential, and have opportunities to grow.
Our employee value proposition (EVP) is about Being Your Best - as a professional and person. It is about being challenged by work that inspires us, being empowered to excel and grow in your career, and being part of a culture where talent is valued. We're a place where everyone can discover and be their best version.

Job Description

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:
. 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 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.

Mandatory Competencies

Data Science and Machine Learning - Data Science and Machine Learning - AI/ML
Beh - Communication
Data Science and Machine Learning - Data Science and Machine Learning - Python
Data Science and Machine Learning - Data Science and Machine Learning - Pytorch
Programming Language - Python - Panda

Perks and Benefits for Irisians

At Iris Software, we offer world-class benefits designed to support the financial, health and well-being needs of our associates to help achieve harmony between their professional and personal growth. From comprehensive health insurance and competitive salaries to flexible work arrangements and ongoing learning opportunities, we're committed to providing a supportive and rewarding work environment.
Join us and experience the difference of working at a company that values its employees success and happiness.

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