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Strong employer brand, metro Bangalore location, and broad ML/big-data skillset increase applicant competition.
Applied airline revenue-management and dynamic-pricing expertise reduces transferability despite general ML skillset.
Explicit 9–12 years plus mandatory ML, big-data, and framework experience makes shortlisting highly strict.
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Design and develop advanced models and real-time optimization algorithms for Dynamic Pricing and Revenue Management to maximize airline revenue.
Build, maintain, and ensure quality of large-scale data pipelines and architectures aligned with business needs.
Train, calibrate, and industrialize machine learning models; conduct analyses, testing, and support customers with model expertise.
9-12 years of experience in Data Science, Machine Learning, or related roles.
Strong programming skills in Python, Java, Scala, and PySpark.
Experience with ML frameworks such as PyTorch, TensorFlow, Keras, and XGBoost, and Big Data technologies including Hadoop and Spark.
Work Experience Required: 9-12 years in relevant fields; Notice Period: Not explicitly mentioned.
Experienced in building and managing ETL pipelines and working with streaming tools like Kafka in large-scale data environments.
Proficient in SQL, MongoDB, data visualization tools (Tableau, Power BI), and familiar with Cloud platforms like Azure and Databricks.
Strong focus on mathematics, modeling, algorithm design, and ability to operate effectively in Agile team settings across functional boundaries.