Data Scientist I

Amazon; Delhi; Presencial; INR 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Amazon Inc. is seeking a data science professional to build and deploy machine learning models for forecasting, anomaly detection, and predictive analytics. You will analyze large datasets, design experiments, and translate business problems into scalable data science solutions.

Collaboration across business, product, and engineering teams is essential. The role involves developing forecasting models for network usage, energy consumption, and operational KPIs, plus creating dashboards and

Formación

• Bachelor’s or master’s degree in computer science, data science, statistics, mathematics, engineering, or related quantitative disciplines.
• Strong proficiency in Python and SQL with hands-on experience in ML frameworks.
• Experience with forecasting, anomaly detection, predictive maintenance, or optimization is desirable.

Responsabilidades

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

Conocimientos

Python

SQL

Scikit-learn

XGBoost

TensorFlow

PyTorch

Statistics

Hypothesis testing

Data visualization

Educación

Bachelor's or Master's in quantitative field

Herramientas

Spark

Hadoop

Power BI

Tableau

Looker

AWS

GCP

Azure

MLOps

Docker

Airflow

Descripción del empleo

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.

Technical Skills:

• 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.
• Excellent communication and presentation skills.
• Experience in telecom or enterprise-scale analytics environments is preferred.

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.