We are looking for a Data Science Engineer / Senior Research Engineer to join our applied AI team at Abhibus. This is a hybrid role at the intersection of AI/ML classical data science and data engineering.
Youll be responsible for:
- Designing and building AI-driven features that power search personalization pricing recommendations and fraud detection.
- Developing robust data pipelines and scalable infrastructure to ensure reliable ML model training and deployment.
- Generating statistical and business insights from large-scale bus travel data to shape product strategy.
- Your work will touch millions of travellers and hundreds of bus operators bringing data- driven innovation to the mobility ecosystem
Key Responsibilities:
- Design and implement ML models for personalization demand forecasting route optimization pricing anomaly detection and recommendations.
- Build maintain and optimize ETL/data pipelines to feed ML models and analytics dashboards.
- Work with product managers & engineers to translate business requirements models production systems.
- Perform statistical analysis A/B testing and causal inference for product & growth experiments.
- Read and adapt academic research papers into practical product applications.
- Ensure model lifecycle management: data collection feature engineering training deployment monitoring and retraining.
- Collaborate with data engineering team on data architecture warehousing and scaling pipelines.
Qualifications :
- Background in Computer Science Engineering or Mathematics (top institutes preferred).
- 26 years of experience in data science & engineering.
- Strong fundamentals in algorithms data structures ML/DL and statistics.
- Proficiency in Python and libraries like TensorFlow/PyTorch Scikit-learn Pandas NumPy SciPy.
- Hands-on experience with SQL and data pipelines (Airflow Spark Kafka dbt or equivalent).
- Ability to translate ambiguous problems into structured models and scalable solutions
Additional Information :
Preferred Skills:
- Experience with cloud platforms (AWS GCP Azure) and ML deployment tools (SageMaker MLflow Kubeflow).
- Knowledge of big data technologies (Spark Hadoop Presto ClickHouse).
- Experience with travel mobility or marketplace problems.
- Contributions to open-source ML or published research
Candidates are responsible for safeguarding sensitive company data against unauthorized access use or disclosure and for reporting any suspected security incidents in line with the organizations ISMS (Information Security Management System) policies and procedures.
Remote Work :
No
Employment Type :
Full-time
We are looking for a Data Science Engineer / Senior Research Engineer to join our applied AI team at Abhibus. This is a hybrid role at the intersection of AI/ML classical data science and data engineering.Youll be responsible for:Designing and building AI-driven features that power search personaliz...
We are looking for a Data Science Engineer / Senior Research Engineer to join our applied AI team at Abhibus. This is a hybrid role at the intersection of AI/ML classical data science and data engineering.
Youll be responsible for:
- Designing and building AI-driven features that power search personalization pricing recommendations and fraud detection.
- Developing robust data pipelines and scalable infrastructure to ensure reliable ML model training and deployment.
- Generating statistical and business insights from large-scale bus travel data to shape product strategy.
- Your work will touch millions of travellers and hundreds of bus operators bringing data- driven innovation to the mobility ecosystem
Key Responsibilities:
- Design and implement ML models for personalization demand forecasting route optimization pricing anomaly detection and recommendations.
- Build maintain and optimize ETL/data pipelines to feed ML models and analytics dashboards.
- Work with product managers & engineers to translate business requirements models production systems.
- Perform statistical analysis A/B testing and causal inference for product & growth experiments.
- Read and adapt academic research papers into practical product applications.
- Ensure model lifecycle management: data collection feature engineering training deployment monitoring and retraining.
- Collaborate with data engineering team on data architecture warehousing and scaling pipelines.
Qualifications :
- Background in Computer Science Engineering or Mathematics (top institutes preferred).
- 26 years of experience in data science & engineering.
- Strong fundamentals in algorithms data structures ML/DL and statistics.
- Proficiency in Python and libraries like TensorFlow/PyTorch Scikit-learn Pandas NumPy SciPy.
- Hands-on experience with SQL and data pipelines (Airflow Spark Kafka dbt or equivalent).
- Ability to translate ambiguous problems into structured models and scalable solutions
Additional Information :
Preferred Skills:
- Experience with cloud platforms (AWS GCP Azure) and ML deployment tools (SageMaker MLflow Kubeflow).
- Knowledge of big data technologies (Spark Hadoop Presto ClickHouse).
- Experience with travel mobility or marketplace problems.
- Contributions to open-source ML or published research
Candidates are responsible for safeguarding sensitive company data against unauthorized access use or disclosure and for reporting any suspected security incidents in line with the organizations ISMS (Information Security Management System) policies and procedures.
Remote Work :
No
Employment Type :
Full-time
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