3 years of experience in Data and Analytics Domain. Overall, 7.5 years of work experience. Experience using ML libraries, such as scikit learn, Seaborn, Matplotlib, Pandas, numpy, RegEx, etc. Experience diving into data …
3 years of experience in Data and Analytics Domain. Overall, 7.5 years of work experience. Experience using ML libraries, such as scikit learn, Seaborn, Matplotlib, Pandas, numpy, RegEx, etc. Experience diving into data to discover hidden patterns. Took ownership of the data science model end-to-end from data collection to model building to monitoring the model in production. Decent understanding of mathematics related to data science probability, statistics, linear algebra, etc. Ability to understand business concerns and formulate them as technical problems that can be solved using data and math/stats/ML. Experience in working as part of a product team, along with engineers and product managers, to define the problem and execute the data science solution. Good interpersonal skills & learning new technologies and undertaking challenges.
Overall, 7.5 years of work experience.
▪ 3 years of experience in Data and Analytics Domain.
▪ Experience using ML libraries, such as scikit learn, Seaborn, Matplotlib, Pandas, numpy, RegEx, etc.
▪ Experience diving into data to discover hidden patterns.
▪ Took ownership of the data science model end-to-end from data collection to model building to monitoring
the model in production.
▪ Decent understanding of mathematics related to data science probability, statistics, linear algebra, etc.
▪ Ability to understand business concerns and formulate them as technical problems that can be solved
using data and math/stats/ML.
▪ Experience in working as part of a product team, along with engineers and product managers, to define
the problem and execute the data science solution.
▪ Good interpersonal skills & learning new technologies and undertaking challenges.
Worked in the Data and Analytics domain.
Used ML libraries such as scikit learn, Seaborn, Matplotlib, Pandas, NumPy, and RegEx.
Dived into data to discover hidden patterns.
Owned the data science model end-to-end from data collection to model building to monitoring the model in production.
Worked as part of a product team with engineers and product managers to define the problem and execute the data science solution.
Applied mathematics related to data science including probability, statistics, and linear algebra.
Understood business concerns and formulated them as technical problems solvable using data and math/stats/ML.
Learned new technologies and undertook challenges.
Received the Professional - Best PB-WD (Golden category) award.
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