Summary of Responsibilities:
- Understanding business objectives and formulate the problem as a Data Science problem
- Expert level proficiency in Multivariate Time Series Forecasting or Causal Forecasting
- Develop and maintain robust data processing pipelines and reproducible modelling pipelines
- Explore data and communicate insights clearly to non-technical as well as technical audience
- Analyze experimental results, iterate and refine models to create significant business impact
- In-depth understanding of classical statistical forecasting algorithms like ARIMA, ETS, etc. as well as new age algorithms like Prophet.
- Proven experience is handling Time Series Forecasting using standard Regression algorithms like Linear Regression, Gradient Boosted Decision Trees, Random forest, etc.
- Good practical knowledge with Sequence Models in Deep Learning, like LSTMs, Transformers, etc. especially in the context of Time Series Forecasting.
- Proficiency with at least one Deep Learning Framework such as PyTorch, Tensorflow, etc.
- Ability to guide and mentor junior Data Scientists on solution development
Desired Skills:
Requirements:
- Bachelor's Degree in a Quantitative discipline, preferably Computer Science
- >4 years' experience in data science/Analytics roles
- Proven experience as a Data Scientist or similar role
- Expert ability to write robust code in Python
- Expert skill at manipulating dataframes using Pandas and arrays using Numpy
- Familiarity with standard machine learning libraries (like scikit-learn , StatsModels)
- Deep Learning Frameworks like Tensorflow, PyTorch etc.
- Completed Projects on Time Series Forecasting, beyond statistical algorithms like ARIMA
- Excellent verbal and written communication skills
- You take complete ownership of your work and are self-driven
Good to Have:
- Familiarity in working with Azure, AWS, GCP etc.
- Experience with NoSQL databases, such as MongoDB, Cassandra
- Experience with containerizing applications using Docker
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