Data Scientist ML
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Role details
Tech stack
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Requirements
Strong hands-on Python and SQL skills for data science (pandas, scikit-learn, and similar). Should be strong in AWS suite, experience working with AWS Cloud or similar environments and tools for Data Science, AI and ML Ability to deploy ML models to production environment. Able to take ambiguous data and turn it into a clear business case, and present that case persuasively to both technical and non-technical audiences. Solid grounding in statistics: hypothesis testing, regression, experimental design (A/B testing). Exposure to GenAI/LLM concepts (RAG, vector databases, prompt engineering) is a plus. Strong predictive, statistical modeling skills. Strong ability to communicate both written and verbally to internal and external clients. Ability to work independently with business users and cross functional leaders. Ability to solve for higher ambiguity using data science. Strong ability to create and deliver effective presentations to multiple audiences. Advanced expertise using data analytic software such as R, Python, SQL. Expert knowledge of Microsoft productivity tools: Excel, Word, and Visio and other software is necessary. Ability to work in a collaborative environment and fast paced environment. Knowledge of Extract Transform Load (ETL), Data Architecture preferred. Ability to mentor junior data scientists and colleagues., Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering or a related quantitative field required. (Masters in related field preferred) 7+ years equivalent experience in modeling, forecasting, data analytics. 3+ years’ experience with AWS (Amazon Web Services) or other cloud platforms. Open-source AI experience preferred. Data Science Certifications Preferred. Certified in AWS Cloud Preferred. Experience in aviation, transportation or IoT/telemetry data domain is a plus
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