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