Sr. Machine Learning Engineer

Job Description:

Accountabilities:

• Research and develop statistical learning models for data analysis
• Collaborate with product management and engineering departments to understand company needs and devise possible solutions
• Keep up-to-date with latest technology trends
• Communicate results and ideas to key decision makers
• Implement new statistical or other mathematical methodologies as needed for specific models or analysis
• Optimize joint development efforts through appropriate database use and project design

Leadership Skills:

• Strong stakeholder management and influencing skills. Able to articulate a vision and build support for that vision in the wider team and organization.
• Ability to self-start and direct efforts based on high-level business objectives
• Strong collaboration and leadership skills with the ability to coach and develop teams to meet new challenges.
• Strong interpersonal, communication, facilitation and presentation skills.
• Work through complex interfaces across organizational and geographic boundaries
• Excellent analytical, planning and problem solving skills
• Utilize an advanced knowledge level of the Data Science Toolbox to participate in the entire Data Science Project Lifecycle and execute end-to-end Data Science project
• Work end-to-end on Data Science developments contributing to all aspects of the project lifecycle
• Should be able to handle big data, structured, unstructured data and manage the data for further analytical processes
• Have an analytical thought process and ability to process complex information.
• Keep customers as focus of analysis insight and recommendation.
• Help define business objectives/customer needs by capturing the right requirements from the right customers.
• Can take defined problems and identify resolution paths and opportunities to solve them; which you validate by defining hypotheses and driving experiments
• Can identify unstructured problems and articulate opportunities to form new analytics project ideas
• Use and understand the key performance indicators (KPIs) and diagnostics to measure performance against business goals
• Compile integrate and analyze data from multiple sources to identify trends expose new opportunities and answer ongoing business questions
• Execute hypothesis-driven analysis to address business questions issues and opportunities
• Build validate and manage advanced models (e.g. explanatory predictive) using statistical and/or other analytical methods
• Are familiar working within Agile Project Management methodologies / structures Analyze results using statistical methods and work with senior team members to make recommendations to improve customer experience and business results
• Have the ability to conceptualize formulate prototype and implement algorithms to capture customer behavior and solve business problems
• Analyze results using statistical methods to make recommendations to improve customer experience and business results
• Demonstrated skill in the use of one or more analytic software tools or languages (e.g., R, Python, Pyomo, Julia/Jump, Matlab, SAS,SQL)
• Demonstrated skill at data cleansing, data quality assessment, and using analytics for data assessment
• End-to-end system design: data analysis, feature engineering, technique selection & implementation, debugging, and maintenance in production.
• Profound understanding of skills like outlier handling, data imputation, bias, variance, cross validation etc.
• Demonstrated skill in modeling techniques, including but not limited to Predictive modeling, Supervised learning, Unsupervised learning, Machine Learning, Statistical Modeling, Natural language processing, Recommendation engines.
• Demonstrated skill in analytic prototyping, analytic scaling, and solutions integration
• Developing hypotheses and set up your own problem frameworks to test for the best solutions
• Knowledge of data visualization tools - ggplot, Dash, d3.js and Matplottlib (or any other data visualization like Tableau, Qlikview)
• Generating insights for a business context

Desirable:

• Experience with cloud technologies for building, deploying and delivering data science applications is desired (preferably in Microsoft Azure)
• Experience in Tensorflow, Keras, Theano, Text Mining is desirable but not mandatory
• Experience to work in Agile and DevOps processes.

Core Skills:

• Bachelor or master degree in information technology, computer science, business administration or a related discipline.
• Certified in Agile Product Owner / SCRUM master and/or other Agile techniques

Interested?