Data Scientist
Company Name:-
ADCI – Karnataka
Job Location:-
Bengaluru, Karnataka
Job Summary:-
5+ years of experience in software development of large-scale data infrastructure and distributed systems
5+ years of experience in data extraction, transformation, statistical analysis and data modeling
5+ years of experience developing enterprise software using Java or Python
3+ years of experience in applying Data Mining and Machine Learning techniques to solve business problems
3+ years of experience using major RDBMS, Hadoop, Spark, Elasticsearch, or similar technologies
3+ years of experience with statistical modeling tools such as R, SAS, SciKit-learn, or TensorFlow
Bachelors degree in Computer Science, Computer Engineering, Machine Learning, or related field or equivalent experience.
Amazon strives to be Earth’s most customer-centric company where people can find and discover anything they want to buy online.
We hire the world’s brightest minds, offering them a fast paced, technologically sophisticated, and friendly work environment.
The FinAuto Anomaly Detection team, part of Finance Automation Org focuses on building application with machine learning models to identify and prevent theft, fraud, abusive and wasteful financial transactions across the company.
As a Data Scientist in the team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the development and business stakeholders through a combination of data mining techniques as well as statistical and machine learning techniques for segmentation and prediction.
You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.
Major responsibilities:Understand the business reality and discover actionable insights from large volumes of data.
Develop statistical and machine learning models to identify theft, fraud, abusive, or wasteful transactions.
Innovate by adapting new modeling techniques and procedures
Use code (Python, SQL, etc.
) to analyze data and build statistical and machine learning models and algorithms.
Identify and prevent theft, fraud, abusive and wasteful transactions.
Partner with developers and business teams to test your models in production.
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