Job Description

Data Scientist/Machine Learning Engineer - Entry/Junior Level SynergisticIT is looking for a Data Scientist/Machine Learning Engineer - Entry/Junior Level in Miami, FL. WHAT MAKES US A GREAT PLACE TO WORK We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We believe that diversity, inclusion, and collaboration are key to building extraordinary teams. We hire people with exceptional talents, abilities, and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. WHAT YOU'LL DO As a member of the growing Data Science and Machine Learning Engineering team, you will: Provide technical expertise for end-to-end technical solution delivery on client cases (from solution architecture to hands-on development work). Develop statistical models to be handed over to clients as prototype or production software. Transform existing prototype code into scalable, production-grade software. Write, test, deploy, and maintain machine learning code across the full software development lifecycle. Collaborate on (or lead) the development of reusable common frameworks, models, and components that can be leveraged to address common engineering problems across industries and business functions. Drive best practices in software engineering and share learnings with team members about theoretical and technical developments in engineering. ABOUT YOU 0-3 years of engineering experience. Proficient knowledge of Python and SQL. Proficiency in one or more of R, Java, C++, Scala, or Django. Fair understanding of fundamental computer science concepts, particularly data structures, algorithms, automated testing, object-oriented programming, and performance complexity. Basic understanding of foundational concepts and algorithms in statistics and machine learning, including NLP, linear/logistic regression, SVM, random forest, boosting, neural networks, dimensionality reduction, and reinforcement learning. Basic knowledge of machine learning frameworks and tools (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, Keras). Basic knowledge of probabilistic programming techniques and associated tools (e.g., Pyro, Stan, TensorFlow Probability, PyMC3), Bayesian inference, and MCMC methods. Please apply to the posting or share your updated resume at [email protected]. No phone calls please. Shortlisted candidates will be contacted. #J-18808-Ljbffr SynergisticIT

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