[San Francisco, CA, .., California, United States | Posted - 05/30/24
Job Description
LinkedIn
Must Haves:
Bachelor's Degree and 2 years exp.
Exp. w/ Machine Learning, analysis, and modeling of large scale and complex data sets in Industry scenarios.
Proficient in Cognitive analytics like text analytics, image recognition, video analytics etc
Python, PySpark, R, SQL, etc. and tools like Databricks, Azure ML and Azure Cognitive Services (at least 2)
Knowledge of DevOps workflows, Git, containers, CI/CD, etc.
What you'll do:??
Customer onboarding, nominations, and vetting processes
Proof of Concept design, lab scheduling, and monitoring of overall governance of AI Studio
Provide Studio tours, manage demo showcase, and process improvements
Conduct customer satisfaction surveys and share key learnings, run customer engagement reports and project retrospective reports as well as provide Studio summary for customer & logging product bugs with engineering team
Produce innovative solutions for our clients driven by exploratory data analysis from complex and high-dimensional datasets, both structured and unstructured, applying advanced statistical, machine-learning and AI techniques.
Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data.
Communicate insights and deliver plans that steer business strategy and decision-making for one or more business segments.
Skills and experiences:
Demonstrable professional experience with applying Machine Learning, analysis, and modeling of large scale and complex data sets in Industry scenarios.
Highly skilled in statistical analysis, quantitative analytics, forecasting/predictive analytics, simulation and optimization algorithms.
Proficient in one or more statistical modeling tools and Cognitive analytics like text analytics, image recognition, video analytics etc.- proficient in model identification by use case/industry and knowledge of applying models to enterprise use cases.
Highly proficient with two or more languages, such as Python, PySpark, R, SQL, etc. and tools like Databricks, Azure ML and Azure Cognitive Services
Software engineering experience using DevOps principals (Knowledge of DevOps workflows, Git, containers, CICD, etc.)
Good communication and presentation skills. Able to explain complex analytical methodologies and concepts in non-technical language to audiences at multiple skill levels.
Bonus Skills: Preference for prior experience working with Azure or cloud-based technologies such as AWS or GCP but not required.
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