Recruitment Team at American Express
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American Express - Research Scientist - Global Servicing Network (1-2 yrs)
Job Description :
American Express has been making a difference in people's lives for over 160 years, backing them in moments big and small, granting access, tools, and resources to take on their biggest challenges and reap the greatest rewards.
We- ve also made a difference in the lives of our people, providing a culture of learning and collaboration, and helping them with what they need to succeed and thrive. We have their backs as they grow their skills, conquer new challenges, or even take time to spend with their family or community. And when they- re ready to take on a new career path, we- re right there with them, giving them the guidance and momentum into the best future they envision. Because we believe that the best way to back our customers is to back our people.
The powerful backing of American Express. Don- t make a difference without it. Don- t live life without it.
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.
Key Responsibilities :
- 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
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