ADCI MAA 15 SEZ
Machine Learning Science, Science, alexa and amazon devices
DataScientist,AlexaConnections
“Data Scientist, Alexa Connections at ADCI MAA 15 SEZ. Skills: Machine learning, Data science, Statistical modeling. Lead development of ML and data science solutions. Power intelligent communication experiences”
What You'll Achieve.
Improve customer engagement; Improve product performance; Demonstrate measurable impact
Industry & Context.
Translate ambiguous problems; Solve business problems; Root cause analysis
What They're Looking For.
Must Have
2+ years of data scientist experience, 3+ years of data querying languages (e. g. SQL), 3+ years of scripting languages (e. g. Python), 3+ years of statistical/mathematical software (e. g. R, SAS, Matlab, etc.) experience, 3+ years of machine learning/statistical modeling data analysis tools and techniques, 1+ years of creating or contributing to mathematical textbooks, 1+ years of creating or contributing to research papers, 1+ years of creating or contributing to educational content
Nice to Have
Ph. D. in Science, Technology, Engineering, or Mathematics (STEM), Knowledge of machine learning concepts, Experience in Python, Experience in Perl, Experience in another scripting language, Experience in a ML or data scientist role with a large technology company, Experience in defining and creating benchmarks for assessing GenAI model performance, Experience working on multi-team, cross-disciplinary projects, Experience applying quantitative analysis to solve business problems, Experience making data-driven business decisions
What You'll Do.
Lead development of ML and data science solutions
Power intelligent communication experiences
Translate ambiguous problems into scalable ML models
Translate ambiguous problems into experimentation frameworks
Translate ambiguous problems into data-driven product decisions
Design advanced ML models
Design advanced statistical models
Deploy advanced ML models
Deploy advanced statistical models
Analyze large-scale datasets
Run rigorous experiments
Improve customer engagement
Improve product performance
Shape applied science roadmap
Deliver AI-driven solutions
Partner with product teams
Partner with engineering teams
Partner with operations teams
Partner with security teams
Translate complex business problems into data science solutions
Translate complex business problems into ML solutions
Own model development lifecycle
Improve models continuously
Define success metrics
Track success metrics
Build data-driven business cases
Prioritize science initiatives
Demonstrate measurable impact
Develop ML-powered systems
Understand customer interactions
Enhance customer experience
Improve data workflows
Publish technical work
Deep dive into business metrics
Build packages in Python
Refine problem statements
Explore model architectures
Leverage AWS services
Solve business problems
Align on solution designs
How You'll Work.
Team & Collaboration
Product teams; Engineering teams; Business leaders; Global cross-functional teams; Sr. Engineers; Principal Engineers; Connections leadership team
Communication Scope
Written communication; Verbal communication
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