Position: Machine Learning Engineer
Company: Access Softek
Experience required: 5y
English level: upper

Access Softek is US-based software development company, started 30 years ago in Berkeley, CA. Today, we have offices opened in New-York city, Chicago, Ohio, Vancouver (Canada) and our head office in California (Berkeley). 

We are hiring an expert Machine Learning Engineer to work with AWS, Google, and Azure ML tools.

You will work primarily with existing tools and techniques, not building new algorithms. You will work with large datasets comprised of bank account data, account history, loan records, end-user personal data, and mobile app interactions. You will need to transform this data into features / data inputs that will be fed into statistical models. You will need to conduct feature transformation, model selection, and model evaluation, and you will need to be able to analyse big volumes of raw data.

The goals of this work include: developing product/loan recommendations, predicting loan risk, identifying good lending options, predicting fraudulent behavior within digital banking channels, etc.

Responsibilities:

— Strong product-oriented person: you should be able to transform your idea from requirements into a MVP.
— Mine and analyse data from databases to drive optimisation and improvement of product development.
— Create MVP of your product solutions.
— Assess the effectiveness and accuracy of data sources and data gathering techniques.
— Develop custom data models and algorithms to apply to data sets.
— Use predictive modeling to increase and optimize customer experience, revenue generation, fraud detection, churn prevention etc.
— Develop processes and tools to monitor and analyse model performance and data accuracy.

Qualifications:

— Strong problem-solving skills with an emphasis on product development.
— Skilled at applying deep neural networks to real world problems.
— Experience using statistical computer languages (R, Python, c#) and working with MS SQL database (querying, prototyping data structures, etc.).
— Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
— Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
— Good written and verbal English, for communication with US-based teams.
— Experience querying databases: MS SQL is preferable.
— Experience with collaboration processes for large teams, including Git flow, Jira, Confluence etc.
— Experience with AWS, Google and Azure machine learning solutions.
— Experience with Deep Neural Networks, such as PyTorch, Tensor Flow and others.
— A drive to learn and master new technologies and techniques.

Our benefits:

— Work from anywhere in the world!
— Competitive salary.
— Compensation vacation (15 day off in a year).
— Global corporate events for all employees.
— Internet compensation (50$ per month).