- Collaborate with cross-functional teams including but not limited to Engineering, Products, Operations, Sales, Marketing, etc. to breakdown complex problems and recommend data science products.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Use machine learning and analytical techniques to create scalable solutions for problems.
- Develop and deploy different ML models and algorithms On production data
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes
What do we need?
- Degree (B.Tech, MS, or equivalent) in Computer Science, Mathematics, Operational Research, Statistics or Natural Sciences
- 1-3 years of work experience in data science and statistical modeling
- Strong problem-solving skills with an emphasis on product development.
- Strong Python skills is a MUST
- Experience working with and creating data architectures.
- Very good understanding of probability and statistics, analytical approach to problem solving, and capability to think critically on a diverse array of problems
- Hands-on experience on statistical methods such as hypothesis testing, Markov laws, time series analysis/ forecasting, etc.
- Very good understanding and hands on experience of building Machine Learning Algorithms such as Logistic Regression, Bayesian Approach, Decision Trees, Support Vector Machines. Tree ensembles etc
- Good presentation skills
- Understanding of advanced algorithms (i.e. Deep Learning, NLP) will be good to have
- Most importantly, an inquisitive mind, an ability for self-learning and abstraction along with a risk appetite for experimentation and failure
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