Founded in 1994, Amazon is now the world's largest online retailer. In a short span of 24 years, they have breached the 1 trillion dollar market cap, making it only the second company to do so. This success of Amazon was made possible owing to its constant pioneering and imbibing of cutting-edge technologies. For instance, Amazon web services which is Amazon’s own machine learning platform, sits on 16 billion dollars worth unrecognised revenue, according to a leading financial daily. The extended contracts by its clients verify the fact that Amazon machine learning services have been top notch. And, it is not surprising if you already are dreaming of working there.
Here we list five of the coolest jobs which will test and hone your machine learning skills:
Program Manager, Analytics
A program manager will work with the Technical team in terms of giving actionable inputs to build intelligent Analytical/Machine Learning models that will drive the quality metrics and use statistical analysis to segment Pricing errors and implement robust Quality Control checks.
- At least 18 months of experience working in Analytics/Machine Learning/Statistical Modeling/Business Intelligence environment.
- Has working knowledge of supervised learning algorithms; Decision trees, ensemble models (Random Forest, bagging and boosting), text analytics (parsing, pre-processing, topic modeling, text classification) and has the ability to build prototypes with quick turnaround using R (dplyr, mlr etc.) or python (pandas, numpy, scipy, scikit learn) and basic knowledge of regression and forecasting techniques.
- SQL, Tableau.
Software Development Engineer
An SDE will be developing scalable solutions using AWS technologies like DynamoDB, SQS, EMR, Lambda, etc to perform such corrections and measure their precision and recall. And, also apply the latest NLP and ML techniques to progressively increase the volume processing automatically without any drop in accuracy.
- A bachelor’s or Master’s degree in Computer Science or a related field with 6+ years of experience in design and development of scalable distributed systems
- Data structures, algorithms and CS fundamentals
- Strong Design and Architecture skills
- Proficiency in Java/C++ or any OO language on a Linux/Unix environment and excellent coding skills.
- Natural language processing and Machine Learning techniques to solve business problems.
Business Intelligence Engineer I
A BIE will build data analytical solutions that will address increasingly complex business questions and will provide descriptive and predictive solutions to the marketing and product management team through a combination of data mining techniques as well as using statistical and machine learning techniques for segmentation and prediction.
Masters required, PhD desired in either Statistics, Economics, Management OR Graduate in Industrial Engineering or Operations Research or Computer Science or a relevant quantitative discipline.
- At least 3+ years of hands-on experience in R, SAS, SQL or similar analytics languages
- Ability to process large data sets from multiple data sources
- Experience in Predictive Analytical modelling such as regression, machine learning, or forecasting using time series or any other such techniques is preferred.
- Between 2 and 3 years’ experience in relational database concepts with a solid knowledge of SQL for data extraction and processing end to end.
Applied Scientist II
This role will require the Machine Learning Scientist to design and deploy scalable algorithms and models that will impact the content visible to millions of customer and also solve key customer experience issues.
- 5+ years of relevant applied science or broad machine learning research experience
- Solid understanding of machine learning, algorithms and computational complexity
- Expert in either Python or Java or C++ or C or Perl/Ruby, etc.
Senior Data Scientist
A senior data scientist will assist customers by being able to deliver a ML / DL project from beginning to end, including understanding the business need. And, use Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help customers build DL models.
- A Bachelor or Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
- 7+ years of industry experience in predictive modelling, data science and analysis
- Experience using Python and/or R and SparkML.
- Experience using ML libraries, such as scikit-learn, caret, mlr, mllib
- Experience working with GPUs to develop models
- Experience giving data presentations.
Register for our upcoming events:
- WEBINAR: HOW TO BEGIN A CAREER IN DATA SCIENCE | 24th Oct
- Machine Learning Developers Summit 2020: 22-23rd Jan, Bangalore | 30-31st Jan, Hyderabad
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A technology journalist with a master's degree in Robotics. Likes to write about machine learning advancements. email:firstname.lastname@example.org