Data Scientist II

Responsibilities:

• Build and deploy machine learning models for forecasting, anomaly detection, predictive maintenance, optimization, and business intelligence use cases.
• Analyze large structured and unstructured datasets to identify trends, business opportunities, and operational inefficiencies.
• Design and execute experiments, A/B tests, and statistical analyses to support strategic decision-making.
• Collaborate with business, product, engineering, and operations teams to translate business problems into scalable data science solutions.
• Develop forecasting models for network usage, energy consumption, infrastructure utilization, and operational KPIs.
• Create automated dashboards, monitoring systems, and scalable data pipelines.
• Improve model performance through feature engineering, hyperparameter tuning, and continuous evaluation.
• Present insights and recommendations to leadership and cross-functional stakeholders.
• Mentor junior analysts/data scientists and contribute to data science best practices.

Requirements:

• Bachelor's or master's degree in computer science, data science, statistics, mathematics, engineering, or related quantitative disciplines.
• Strong proficiency in Python and SQL.
• Hands-on experience with Scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Strong understanding of statistics, probability, hypothesis testing, and predictive modeling.
• Experience with Spark, Hadoop, or distributed computing frameworks.
• Expertise in Power BI, Tableau, or Looker.
• Familiarity with AWS, GCP, or Azure is preferred.
• Knowledge of MLOps, Docker, Airflow, or deployment pipelines is a plus.

Functional Skills:

• Strong analytical and problem-solving mindset.
• Ability to independently drive projects and collaborate with stakeholders.

Preferred Experience:

• 3-5 years of experience in data science, machine learning, or advanced analytics.
• Experience in forecasting, optimization, anomaly detection, or predictive analytics.
• Exposure to telecom/network analytics, IoT analytics, or infrastructure operations is an added advantage.