Data Science Engineer

As a Data Science Engineer at Exela, you will be a key member of our dynamic team, responsible for designing, developing, and deploying scalable data science solutions to address real-world problems. With over 5 years of experience, you will play a crucial role in building end-to-end machine learning pipelines, integrating data science solutions into production systems, and collaborating with cross-functional teams to derive business value from data. Your responsibilities will include: Data Engineering: - Developing and maintaining ETL pipelines to pre-process and clean data from various sources. - Designing and optimizing data storage solutions for analytics and machine learning use cases. - Collaborating with data engineers to ensure seamless data flow. Machine Learning & Analytics: - Developing, training, and deploying machine learning models to solve business challenges. - Conducting exploratory data analysis (EDA) to derive actionable insights. - Monitoring and retraining models to ensure performance and relevance over time. Production Deployment: - Designing scalable, reliable, and efficient systems to deploy machine learning models into production environments. - Implementing APIs or integrating models into existing business workflows. Collaboration & Communication: - Working closely with product managers, data analysts, and business stakeholders to align technical solutions with business objectives. - Presenting findings, insights, and solutions to both technical and non-technical audiences. Continuous Improvement: - Staying up-to-date with advancements in data science, machine learning, and big data technologies. - Conducting peer code reviews and ensuring adherence to best practices. Requirements: - Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. - Experience in Healthcare domain projects. - Proficiency in programming languages such as Python, R, or Java. - Hands-on experience with data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). - Expertise in SQL and working with relational databases. - Experience with cloud platforms (AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes). - Familiarity with version control tools (e.g., Git). - Knowledge of containerization tools like Docker and orchestration tools like Kubernetes is a plus. - Familiarity with CI/CD pipelines and version control systems like Git. - Understanding of data governance, security, and compliance requirements. - Experience with big data technologies (e.g., Spark, Hadoop). - Knowledge of deep learning techniques and natural language processing (NLP). - Strong understanding of MLOps and model lifecycle management. - Proficiency in data visualization tools (e.g., Tableau, Power BI, Matplotlib). Join Exela's global team and be a part of the revolution in business process automation solutions that impact our clients" mission-critical operations across various industries. Your expertise and innovative ideas will contribute to the success and growth of our organization.,