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Research Scientist - Big Data/Machine Learning Practices
American Express for 9th consecutive year has been voted among India’s top 10 workplaces by the Great Place to Work institute. In recognition of our consistent performance, we were nominated to the Great Place to Work “Hall of Fame”.
At American Express, we serve customers, not transactions. We’re widely known for providing superior customer service and have been recognized for a number of achievements including being ranked highest in customer satisfaction within the credit card industry by J.D. Power for seven consecutive years.
A career at American Express is rich in experience and offers opportunities to build lasting relationships with our customers.
Come join us and realize your potential.
This position is within the Global Servicing Network (GSN) Big Data & Machine Learning practice. The role holder will be a subject matter expert in Machine Learning in Big Data environment and work closely with other stakeholders for continuous delivery.
At GSN Big Data ML team, we are solving few key challenging Machine Learning problems including Text and voice based predictive customer journeys, optimizing customer Servicing Channels and adding significant value to the servicing capabilities of the organization.
• Regularly engage with business teams to understand their needs and imperatives and operationalize a framework for deploying Machine Learning models
• Prototype and simulate use cases for Machine learning basis the GSN operating environment and ability to operationalize into workable algorithms & solutions.
• Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business.
• Deploy models in production environment and regular maintenance of production variables like Lift, Support, Confidence and continuous bootstrapping of sample cases for revalidation of results.
• Capability of writing, debugging and compiling codes in multiple Machine Learning environment and not limited to Python/Pyspark, Apache Spark, R Spark etc.
At least 1-2 years of experience in the following areas.
1. Complete grip on Python environment and libraries (scikit, nltk, pandas and numpy). Working knowledge of R & Spark is a plus.
2. Proven experience of solving complex business problems using Machine Learning techniques like Regression, Classification, Supervized or Unsupervized Recommenders, Deep iterative learning, Neural Nets etc.
3. Deep knowledge of Statistics and Maths and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable
4. Experience of working in Distributed/Cluster computing environment is desirable
5. Ability to work in cross functional teams
6. Excellent data presentation and visualization skills
7. Hands on knowledge of SQL/ Hive QL is desirable
Schedule (Full-Time/Part-Time): Full-time