• Implement machine learning, data mining, statistical, and graph-based algorithms designed to analyze massive data sets
• Implement new data modeling solutions and improvements to existing solutions
• Integrate new data sources and API third-party products in the main framework
• Work with Big Data technologies using Spark
• Provide analytical support to the data science team
• Own and drive projects from conception to completion
• Collaborate with data scientists, engineers and other key stakeholders
• Manage feature engineering lifecycle including prototyping, validating, maintenance of features.
• Partner with Cloud technologists to ensure proper implementation and usage of said algorithms
• Work well in a fast-paced cross-functional environment
• Analyze large data sets to develop multiple, custom models and algorithms to drive innovative correlations for fraud and acceptance data as well as social data

Qualifications:

• BE/B.TECH/ME/MSc in computer science, industrial engineering, electrical engineering, operations research, mathematics, statistics or similar or equivalent work experience.
• 2- 4 years of industry experience working in a similar role
• Experience in data-driven algorithms in information retrieval, relevance, or machine learning and working with distributed systems.
• Strong Python/R programming background
• Big data tools using spark (Scala or Python) in distributed systems.
• Good working knowledge of SQL
• AWS (s3, emr, aws cli minimum)

Preferred:

• Dashboard development experience (Dash, Bokeh, R Shiny)
• Experience with data workflow managers such as Airflow, Drake, or Luigi
• Experience in advanced analytics and developing machine learning models
• Programming experience in Scala, Java
• Experience with containerization (Docker)
• Experience with cloud ecosystems such as Microsoft Azure, Google Cloud Platform or Amazon Web Services