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.
If you have a strong will to learn and educate and are motivated by the opportunity to help grow our team and be a part of an industry-leading technology and innovation organization, then look no further! There are hundreds of opportunities to make your mark on technology and life at American Express.
American Express is embarking on an exciting transformation on building the next generation customer first ecosystem for democratizing Machine Learning in Amex on the Cloud. You will be part of an energetic Data Science/Machine Learning team, to drive strategic planning and a cohesive set of technology and machine learning solutions enabling data and platform transformation, by collaborating across all channel teams and the critical technology platforms that support Colleague and Customer Experiences. This position provides you an opportunity to solve very interesting problems that directly and greatly impact millions of individuals worldwide. If you have the talent and desire to deliver innovative and intelligent products as well as services at a rapid pace, serving our colleagues and customers seamlessly across through cognitive solutions, this would be the right fit for you!
Your responsibilities would include:
- More than 70%+ of the time spent on coding and/or hands-on technical implementation of re-usable frameworks to drive adoption of Machine Learning in the Enterprise
- Leading your own project. Suggesting, collecting and synthesizing requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.
- Architecting, estimating and planning technical solutions to problems
- Implementing new, highly scalable platform components and tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing and Time Series predictions
- Actively participating in team and company-wide architecture and engineering discussions and forums
To be successful in the role, the following experience is required:
At least 1-2 years of experience in the following areas:
- Master of Science or higher in a quantitative discipline, e.g. Data Science, Statistics, Mathematics, Computer Sciences or similar Bachelor of Science with 1-2 years of experience in a highly quantitative position
- Firm grip of Python environment and 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 Maths, and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable.
- Experience of working in Distributed/Cluster computing environment is desirable
- Ability to work in cross functional teams
- Excellent data presentation and visualization skills
- Hands on knowledge of SQL/ Hive QL is desirable
- Demonstrate self-reliance to achieve goals collaboratively
- Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems.
- Thought leadership and innovative thinking
Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions.
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Feb 4, 2020, 5:18:08 PM