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Iris Software
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Data Science - Lead

Data Science - Lead

Iris Software

5 - 10 years

10 - 15 Lacs

Noida

Posted:2 days ago| Platform:

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Skills Required

aiml machine learning artificial intelligence tensorflow ml algorithms python ai solutions scikit-learn dbms sql configuration management java data science ecs spark devops database creation kafka pytorch data structures software engineering aws

Work Mode

Work from Office

Job Type

Full Time

Job Description

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.

Mandatory Competencies

Data Science and Machine Learning - Data Science and Machine Learning - AI/ML

Database - Database Programming - SQL

Artifical Intelligence - AI Tools - TensorFlow

Cloud - AWS - ECS

DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Containerization (Docker, Kubernetes)

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