Director - Human Capital at Fractal Analytics
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Fractal Analytics - Senior Data Scientist - Machine Learning & Artificial Intelligence (4-8 yrs)
We are looking for candidates who are passionate about solving complex computational problems by writing cutting edge algorithms/programs and are interested in applying this to huge datasets to build large scale data analytics products and solutions. You will innovate, design, analyze, evaluate, architect and implement complex algorithms and machine learning models operating on large data sets.
- An ideal candidate will enjoy working with large data and finding interesting patterns in the data through analytics experiments in a methodical and scientific data-driven way.
- Deploy state-of-the-art, data-driven learning algorithms to solve business problems using the latest technologies in neural networks, NLP, machine learning, statistical modeling, pattern recognition, and artificial intelligence
- Dig deeper into data, understand characteristics of data, evaluate alternate models and validate hypothesis through theoretical and empirical approaches
- Own complete development and designing of the algorithms and frameworks involved in the same
- Conduct design and code reviews, productize proven or working models into production quality code
- File patents for innovative solutions and write technology paper
- Use techniques from artificial intelligence/machine learning to solve supervised and unsupervised learning problems
Demonstrable experience between 4 to 8 years designing ML/statistical solutions to complex business problems at scale; developing & testing modular, reusable, efficient and scalable code to implement those solutions.
Ideally, this would include the following:
- High proficiency in concepts and algorithms used in design of experiments.
- Expert-level proficiency in at least one of R or Python's (preferred) data science stack
- Expert-level proficiency in statistical/ML predictive techniques such as regression, Bayesian methods, tree-based learners, SVM etc
- Good to have working experience in one or more of Probablistic graphical models, Reinforcement learning, NLP and related areas
- Demonstrable experience of formulating a problem statement and implementing analytical solutions by understanding available data and functional requirements
- Thorough grasp on RDBMS and data management concepts as well as fluency in SQL scripting
- Fair understanding of distributed computing in multicore and/or clusters, especially using R/Python
- Operating knowledge of cloud computing platforms (AWS, especially EMR, EC2, S3, and the AWS CLI)
- Experience working within a Linux computing environment, and use of command line tools for automating common tasks
- Ability to work in a team in an agile setting, familiarity with JIRA and clear understanding of how version control software works, especially Git
- In addition, the ideal candidate would have great problem solving skills, and the ability & confidence to hack their way out of tight corners.
Education: PHD/ MS / M.Tech (preferred) or BS / B.Tech. in a field with significant quantitative training such as Statistics, ML, AI, Physics, Mathematics, Economics, Finance etc.
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