Data Scientist with career break - Woman

As a Data Scientist at our company, your primary responsibilities will include: - Understanding Business problems and KPIs by holding discussions with relevant customer stakeholders - Prescribing the right data science approach to solve customers Business problems - Identifying the different data sources needed for project execution including both internal and external data - Ensuring proper DQ checks are done and the data is well understood by the Team - Documenting DQ related issues and barriers and taking them up with Customer stakeholders - Generating hypothesis for performing various Exploratory analysis and leading the effort - Storyboarding the findings in data and explaining the Business value convincingly to customers - Driving analytical modeling using a variety of learning algorithms and ability to compare model outputs without Bias - Demonstrating Business value of Analytical models and ensuring they are deployed in Production - Prescribing the right Data technologies to use in Production and leading the Data pipelining effort for production - Orchestrating Data and ML solutions using Cloud services - Employing CI/CD practices in Model deployment and producing a state-of-art model deployment that can be Traceable - Being the anchor for Customer calls and ensuring customer communication is effective - Ensuring that right coding guidelines and processes are followed by the Team - Institutionalizing good Data Science practices in the Team - Ensuring proper documentation via good project management tools like Confluence, JIRA etc. - Authoring Technical blogs both internally and externally and evangelizing the Teams efforts Your qualifications should include: - BS/MS in Computer Science, Math, Physics, Engineering, Statistics or other quantitative or computational field. Advanced degrees preferred - Knowing what model to apply and in what situation to apply (know advantages and disadvantages of ML /DL techniques) - Proven ability to perform in-depth analysis, compile and interpret results - Demonstrating proficiency with various approaches in regression, classification, and cluster analysis - Good understanding of applied statistics, such as probability distributions, measures of dispersion and central tendency, hypothesis testing and statistical inferences - Demonstrating proficiency in at least one Deep learning technologies - Demonstrated Experience in at least in one of the following NLP/computer vision/operations research/data mining/ML/AI - Must have experience ML models in R/ Python - Demonstrable strength in programming in Python/R/Scala - Having good experience in Object-oriented technologies and Design - Experience with one or more data visualization tool / library such as Tableau, R Shiny, Seaborn, etc - Expertise in SQL programming languages and familiarity with Hive, Pig - Excellent quantitative skills and the ability to tell a story using data - Strong communication and presentation skills - Ability to initiate and drive projects from conception to completion with minimal guidance - Passionate about turning data into actionable insights It would be good to have: - M.S. in Computer Science, Math, Physics, Engineering, Statistics or other quantitative or computational field - Expertise in the application of machine learning algorithms on large datasets - Experience with large datasets and distributed computing (Hadoop, Spark) a plus - Experience accessing data, map-reduce programming style and training models in Hadoop, Spark - Experience in deploying models in cloud platforms such as Google Cloud/Microsoft Azure/AWS is a plus - Nice to have knowledge of NoSQL DBs like MongoDB, Cassandra and HBase - Contribution to research community reflected in publications in top conferences/Kaggle competitions - Knowledge of latest DL technologies Your personal attributes should include: - Strong written and verbal communication skills - Articulation skills - Good team player - Self-starter who requires minimal oversight - Ability to prioritize and manage multiple tasks - Process orientation and the ability to define and set up processes As a Data Scientist at our company, your primary responsibilities will include: - Understanding Business problems and KPIs by holding discussions with relevant customer stakeholders - Prescribing the right data science approach to solve customers Business problems - Identifying the different data sources needed for project execution including both internal and external data - Ensuring proper DQ checks are done and the data is well understood by the Team - Documenting DQ related issues and barriers and taking them up with Customer stakeholders - Generating hypothesis for performing various Exploratory analysis and leading the effort - Storyboarding the findings in data and explaining the Business value convincingly to customers - Driving analytical modeling using a variety of learning algorithms and ability to compare model outputs without Bias - Demonstra