Proficient knowledge of Python and SQL; familiarity with one or more of R, Java, C++, Scala, or Django.
Strong understanding of CS fundamentals (data structures, algorithms, automated testing, object-oriented programming, performance), and basic statistics and ML concepts (NLP, linear/logistic regression, SVM, random forest, boosting, neural networks).
Basic knowledge of machine learning frameworks and tools (Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, Keras, Huggingface) and probabilistic programming/bayesian methods (e.g., Pyro, Stan, TensorFlow Probability, PyMC3).
Requirements:
Provide technical expertise for end-to-end solution delivery on client cases from solution architecture to hands-on development.
Develop statistical/models to be handed over to clients as prototypes or production software.
Transform existing prototype code into scalable, production-grade software and maintain ML code across the full software development lifecycle.
Collaborate on or lead the development of reusable frameworks, models, and components to address cross-industry engineering problems.
Job description
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.
SYNERGISTICIT wants every Job seeker to be aware that the Job Market is Challenging and to stand out you need to have exceptional skills and technologies which make you stand out from other Job seekers.
If your skills and your project work are similar to others then it's difficult to stand out to the clients. Since 2010 we have helped Jobseekers stand out by ensuring only the best candidates with the requisite skillset go to the clients and get the attention that they need. We just don't focus on getting you a Job we make careers.
We have an excellent reputation with the clients. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists. WHAT YOU'LL DO
As a member of the growing Data Science and Machine Learning (Client) Engineering team in Bain's Advanced Analytics Group, 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/Client 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 re-usable common frameworks, model and components that can be highly leveraged to address common Client engineering problems across industries and business functions
Drive best demonstrated practices in software engineering, and share learnings with team members in SynergisticIT about theoretical and technical developments in Client 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, Django
Fair understanding of fundamental computer science concepts, particularly data structures, algorithms, automated testing, object-oriented programming, performance complexity, and implications of computer architecture on software performance
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, reinforcement learning, etc.
Basic Knowledge of machine learning frameworks and tools (e.g. Pandas, numpy, scikit-learn, TensorFlow, Pytorch, Keras, Huggingface)
Basic Knowledge of probabilistic programming techniques and associated tools (e.g. Pyro, Stan, Tensorflow Probability, PyMC3), Bayesian inference and MCMC methods
