Data Scientist & ML developer

Key Responsibilities Data Collection & Analysis • Gather and analyze data from diverse source systems (databases, spreadsheets, etc.). • Ensure data is clean, accurate, complete, and ready for prediction tasks. • Analyze datasets to uncover patterns, correlations, anomalies, and business insights. Model Development & Deployment • Design and develop ML models (supervised, unsupervised, reinforcement learning, etc.) based on business requirements (e.g., customer recommendations). • Train, test, and validate models using real-world data. • Deploy machine learning models into production environments and monitor their performance. Visualization & Communication • Present insights and outcomes using charts, graphs, dashboards (e.g., Matplotlib). • Collaborate with customers and local teams to understand problems, define requirements, and communicate results effectively. Technical Execution • Design and develop Python programs and FastAPI-based microservices. • Work across Linux and Windows platforms for development and deployment. • Maintain strong code quality, documentation, and testing procedures. • Debug, optimize, and enhance existing ML models and services. Collaboration & Mentoring • Act as a mentor and technical guide to team members. • Work in tandem with customer-facing teams to ensure solution alignment and success. • Follow professional service lifecycle processes including scoping, requirements gathering, development, QA / testing, and deployment. Required Qualifications & Skills Education • Bachelor's or Master's degree in Computer Science, ECE, EEE, EI, IT, or a related field. Experience • 4 to 8 years of software consulting experience in enterprise software solutions, including direct customer interaction. • Hands-on experience with machine learning in real use cases, deployed in commercial systems. Technical Skills • Proficiency in Python, PostgreSQL, SQL. • Expertise in Pandas, NumPy, Scikit-learn, and FastAPI. • Experience with data transformation, pattern recognition, and feature engineering. • Strong knowledge of machine learning algorithms : • Regression, Decision Trees, Random Forests, Bayesian Methods, Neural Networks, etc. • Ability to choose appropriate algorithms based on use cases. • Knowledge of statistics, probability, and linear algebra for model building. • Experience developing on both Linux and Windows platforms. • Strong design, implementation, debugging, and troubleshooting skills. Domain Expertise • Experience in Telecom Software Domain, especially OSS and Configuration Management (CM). Soft Skills • Strong written and verbal communication skills. • Ability to work independently and in collaborative, cross-functional teams. • Strong mentoring and team leadership capabilities. Skills Required Machine Learning, Data Science, Python, Pandas, Numpy