- Excellent understanding of machine learning techniques and algorithms
- Proficiency with R/ Octave for modeling, Python & Java for production-ready code.
- Experience with common data science toolkits, such as R/ Octave for modeling, Python & Java for production-ready code. Excellence in at least one of these is highly desirable.
- Experience with data visualization and extracting insights from them.
- Proficiency in using query languages such as SQL, Learning in the area of NLP, predictive models & recommendation engines is a big plus
- Crunch a large volume of data, observe trends and build scalable & analytical models.
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Good scripting and programming skills
- Data-oriented personality
- Good knowledge of databases like NoSQL, MongoDB, Postgre, etc.
- Perform Exploratory Data Analysis and Statistical Analysis; clearly present the results of an analysis to customers and management.
- Experience with AWS, Google Cloud is a plus
- Exposure with deep learning algorithms is a big plus
- Selecting features, building and optimizing models using machine learning techniques
- Data mining using state-of-the-art methods
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
- Adopting new research methodologies including deep learning (CNNs LSTMs) on projects
- Bachelors/ Masters in Computer Science or Electronics from tier 1 & 2 colleges