American Express Careers
Senior Machine Learning Engineer
Why American Express
There’s a difference between having a job and making a difference.
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 Group Technology (GSGT) Credit & Fraud Big Data & Machine Learning practice. The person will be a subject matter expert in Machine Learning in Big Data environment and work closely with other stakeholders for continuous delivery.
At GSGT Credit & Fraud Big Data team, we are working on some key challenging Machine Learning problems including text analytics, optimizing collection channels and adding significant value to the Credit & Fraud 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 GSG 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.
Position requires a Master’s degree in Statistics, Mathematics, Econometrics, Data Science, Operations Research, or a related field, and at least 2 years of experience in the following areas:
- Expertize in Python environment and associated libraries (scikit, nltk, pandas and numpy). Working knowledge of R & Spark is a plus.
- Proven experience of solving complex business problems using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep iterative learning, Neural Nets etc.
- Deep knowledge of Statistics and Mathematics and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics and Group theory is desirable.
- Experience must include a minimum of one year of experience with translating data-based findings into non-technical recommendations on strategic business decisions and presenting recommendations to leadership.
- Experience of working in Distributed/Cluster computing environment is desirable.
- Ability to work in cross functional teams.
- Excellent communication skills and ability to interact with top management to discuss and deep dive on ML use cases.
- Excellent data presentation and visualization skills.
- Hands on knowledge of SQL/ Hive QL is desirable.
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Mar 12, 2019, 10:19:38 AM