Data Scientist (Developer)

Job Description: Job Title: Data Scientist (Developer) Role: Data Scientist (Developer) Experience: 4-7 years (minimum 3 years in AI/ML) Location: Work From Office (WFO) - Hyderabad Notice Period: Immediate to 15 days Key Responsibilities: 1 AI/ML Model Development: Design, develop, and implement advanced machine learning algorithms and AI models to solve complex business problems. Perform model selection, hyperparameter tuning, and optimization to ensure high performance and scalability. 2 Data Analysis and Preparation: Extract, clean, and preprocess data from various sources for analysis. Perform exploratory data analysis (EDA) to uncover trends, patterns, and insights. 3 Deployment and Maintenance: Deploy models into production environments and ensure their seamless integration with existing systems. Monitor model performance and retrain as necessary to maintain accuracy. 4 Collaboration: Work closely with cross-functional teams, including data engineers, software developers, and business stakeholders, to align AI/ML solutions with organizational goals. 5 Documentation and Reporting: Document workflows, processes, and findings comprehensively. Present results and insights to stakeholders in an understandable format. Qualifications and Skills: Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. Requirements: ? Proficiency in programming languages: Python, R, or Java. ? Hands-on experience with machine learning libraries and frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, etc. ? Strong knowledge of data preprocessing tools and libraries: Pandas, NumPy, and OpenCV (for computer vision tasks). ? Familiarity with databases and query languages: SQL, NoSQL. ? Experience with big data technologies: Hadoop, Spark (is a plus). ? Cloud platforms experience: AWS, GCP, or Azure (especially for AI/ML services). ? Knowledge of version control tools such as Git. Technical Skills Programming Languages: Python, R, Java | Machine Learning Libraries/Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras | Data Preprocessing Tools: Pandas, NumPy, OpenCV (for computer vision tasks) | Databases: SQL, NoSQL | Big Data Technologies: Hadoop, Spark (is a plus) | Cloud Platforms: AWS, GCP, Azure (especially for AI/ML services) | Version Control Tools: Git "