Senior Data scientist
6 months ago
Number of Position: 1
Experience: 5+ years (thorough)
Reports to: Principal Solutions Architect/Technical Project Manager
Job Responsibilities:
Ship high-quality, well-tested, secure, and maintainable codeDesign, develop, and maintain data pipelines and back-end services for real-time decisions, reporting, optimization, data collection, and related functionsManage automated unit and integration test suitesWork collaboratively and communicate effectively with a small, motivated team of engineers and product managersExperiment with and recommend new technologies that simplify or improve Microsoft stackWork closely with Data Scientists to optimize and reengineer model code to be modular, efficient, and scalable, and to deploy models to production.Build visualizations to help derive meaningful insights from dataMaintain and enhance our data and computation platformDevelop and implement solutions for data quality validation and continuous improvement.Partner with data scientists, PMs, engineers, and business stakeholders to understand business and technical requirements, plan and execute projects, and communicate status, risks, and issues.Perform root cause analysis of system and data issues and develop solutions as required.Applying statistical and machine learning techniques to problems like text feedback analysis, customer/user segmentation/classification to understand usage trends and drivers of satisfactionsDesign experiments, analyze results and produce actionable, trustworthy conclusions from themPresent findings and recommendations to key decision-makers at various management levelsLeverage the Data Science and Machine Learning, to experiment with and establish new ways of driving customer engagement by leveraging data – ultimately resulting in usage and satisfaction growthBuild data manipulation, processing, and data visualization tools and share these tools across the team and using Microsoft Technologies.Leverage your statistical and computational knowledge to build algorithms for calculating variances.Apply data analysis, data mining and data engineering to present data clearly and develop experiments (A/B testing)Ensure high-quality data and understand how data is generated out experimental design and how these experiments can produce actionable, trustworthy conclusions.Work with development teams to build tools for data logging and repeatable data tasks that will accelerate and automate data scientist duties.-
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