Description

About S3B Global Technologies LLP S3B Global Technologies is a cutting-edge technology consulting and digital transformation company. The organization specializes in delivering bespoke IT solutions and end-to-end digital transformation services for enterprise clients across industries. With a strong focus on innovation, scalability, and modern cloud technologies, S3B Global helps businesses drive efficiency and long-term value through data-driven solutions. Job Summary S3B Global Technologies is seeking a highly skilled Data Scientist (ML) with strong Python expertise and hands-on experience in machine learning and MLOps. The ideal candidate will work on designing, developing, and deploying scalable ML solutions using modern cloud platforms and automation tools. This role requires strong analytical thinking, problem-solving ability, and effective communication skills. Key Responsibilities Design, develop, and deploy machine learning models using Python Apply ML techniques such as forecasting, clustering, regression, classification, and optimization Develop clean, modular, and scalable code using advanced Python and OOP principles Build and manage data pipelines and ML workflows using Airflow Implement and maintain MLOps practices, including model tracking, monitoring, and deployment Work with Azure cloud services, Databricks, Spark, and MLflow Containerize ML applications using Docker for scalable deployment Collaborate with cross-functional teams to translate business problems into ML solutions Use Git for version control and collaborative development Ensure high-quality documentation and reproducibility of models and workflows Communicate technical insights effectively to both technical and non-technical stakeholders Required Qualifications Bachelor’s or Master’s degree in any discipline (UG/PG) 1–6 years of hands-on experience in Data Science and Machine Learning Strong proficiency in Python, including Object-Oriented Programming (OOP) Practical experience with machine learning algorithms and predictive modeling Exposure to Natural Language Processing (NLP) and Deep Learning concepts Experience with Azure cloud platform and Databricks Hands-on knowledge of MLflow for experiment tracking and model lifecycle management Experience with Apache Airflow for workflow orchestration Knowledge of Docker and containerization concepts Experience using SQL and big data frameworks such as Spark Familiarity with Git and version control best practices Key Skills & Competencies Python (Advanced) & OOP Machine Learning & Artificial Intelligence Forecasting, Clustering, Regression, Classification Deep Learning & Neural Networks NLP (Preferred) Azure Cloud, Databricks, Spark MLOps, MLflow, Docker Apache Airflow SQL & Data Engineering Basics Strong Problem-Solving Skills Excellent Communication & Presentation Skills

Role and Responsibilities

• Key Responsibilities Design, develop, and deploy machine learning models using Python Apply ML techniques such as forecasting, clustering, regression, classification, and optimization Develop clean, modular, and scalable code using advanced Python and OOP principles Build and manage data pipelines and ML workflows using Airflow Implement and maintain MLOps practices, including model tracking, monitoring, and deployment Work with Azure cloud services, Databricks, Spark, and MLflow Containerize ML applications using Docker for scalable deployment Collaborate with cross-functional teams to translate business problems into ML solutions Use Git for version control and collaborative development Ensure high-quality documentation and reproducibility of models and workflows Communicate technical insights effectively to both technical and non-technical stakeholders