Senior Machine Learning Engineer

Primary Responsibilities

• Build machine learning models in open source packages like Python and deploy using cloud infrastructure available in Amazon Web Services
• Understand the business requirement and suggest / evaluate the right features and technique best suited to train and test the model.
• Work on feature engineering to ensure most information going into the model for prediction accuracy.
• Work with cloud architecture and digital development team to deploy the model online and offline
• Work with testing team to design the test online or offline and work towards improving the model based on test results
• Collaborate with internal stakeholders to understand the business strategy and work towards supporting that by gathering the right data and building machine learning models.
• Follow machine learning model management and lifecycle best practice for all Artificial Intelligence and Machine Learning models created

Education & Experience

• Level of Formal Education : Masters degree or equivalent experience
• Area of Study : statistical analysis, computational sciences, mathematics, physics or econometrics
• Years of Experience : 3-5 Years of experience
• Type of Experience : Experience in data modeling, data engineering, feature engineering, model lifecycle management and experience with cloud infrastructure
• Special Certifications : (CPA, Etc.) Mathematics Business Intelligence AWS Open source frame works and Statistical Modeling
• Language Skills : English
• Technical Competencies : SQL, R, Python, Deep Learning, NoSQL technologies, Hadoop, Anaconda, Tableau, Excel, Analysis, Database Concepts, Kubernetes Infrastructure including Kube Flow, using Docker for containerization.
• Strong Knowledge of supervised and unsupervised deep learning algorithms like CNN, RNN, GRU and experience in advanced deep learning packages like TensorFlow, Keras, Pytorch, Caffe, Theano etc.

Experience in data visualization packages in Python or other languages required

Skills and Abilities : Selecting analytics tools to manage model lifecycle across groups and be experienced in open source tools like Python, R, Tensorflow, keras (Deep learning libraries) etc.

Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy Practical experience with Business analysis, Data extraction in SQL and data analytics Experience in writing SQL against complete data warehouse systems with multiple takes.

Teradata experience is a plus. Experience implementing a Recommendation Engine (knowledgeable on collaborative filtering and content-based filtering) and working on Web Analytics.

Experience in applying Deep Learning to time series analysis (including ARIMA, ARMA and survival analysis) Strong understanding of experimental and test-and-learn design concepts and application.

Experience with analyzing big data sets using Hadoop, Spark and open source technologies Experience working with third party data providers like DNB, Acxiom, Info group to utilize firmographic, psychographic and demographic data Experience in Retail Industry is a plus.

Extensive background in statistical analysis, computational sciences, mathematics, physics, or econometrics.

Information Systems : People Soft, R, Python, Anaconda, SQL, NoSQL, Hadoop, Spark, Databricks, H2O, Tableau, Excel, Analysis.

Disclaimer

The above statements are intended to describe the general nature and level of work being performed by associates assigned to this classification and are not intended to be a complete list of all responsibilities, duties and skills required of associates so classified.

Other duties may be assigned.

Pay, Benefits & Work Schedule

The company offers competitive salaries, a benefits package, which includes a 401(k) and more, along with plenty of opportunity to move and grow within our organization!