Your Role and Responsibilities

• Master’s degree in a quantitative field such as computer science, applied mathematics, statistics, physics, engineering or finance
• Overall Data Science, Statistical Analysis, Data Analytics & Machine Learning experience of 2-3 + years
• Good knowledge of applied methods in statistics, machine learning and artificial intelligence
• Good understanding of various AI/ML technology stacks including Cloud Based services
• Experience in natural language processing, text analytics, data mining, text processing or other AI subdomains and techniques
• Good data management and statistical modelling skills
• Experience with Scala/Python, Scikit-learn, TensorFlow, Keras, NLTK, PyTorch etc
• Experience with leveraging best practices conducting advanced analytics projects
• Experience in distributed & scalable ML development. Good PoV on TinyML and Embedded AI/ML
• Apply data analysis, data mining and data engineering to present data clearly and develop experiments (A/B testing)
• Work with development teams to build tools for repeatable data science tasks that will accelerate and automate data scientist workflows
• Ability to mine and analyze data from various sources to solve clients problems within multiple domains like marketing, HR, supply chain, operations, sales etc
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Coding knowledge and experience with several languages: C, C++, Java,
• JavaScript, etc.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, tableau, power BI, looker etc.

Required Technical and Professional Expertise

• Master’s degree in a quantitative field such as computer science, applied mathematics, statistics, physics, engineering or finance
• Overall Data Science, Statistical Analysis, Data Analytics & Machine Learning experience of 2-3 + years
• Good knowledge of applied methods in statistics, machine learning and artificial intelligence
• Good understanding of various AI/ML technology stacks including Cloud Based services
• Experience in natural language processing, text analytics, data mining, text processing or other AI subdomains and techniques
• Good data management and statistical modelling skills
• Experience with Scala/Python, Scikit-learn, TensorFlow, Keras, NLTK, PyTorch etc
• Experience with leveraging best practices conducting advanced analytics projects
• Experience in distributed & scalable ML development. Good PoV on TinyML and Embedded AI/ML
• Apply data analysis, data mining and data engineering to present data clearly and develop experiments (A/B testing)
• Work with development teams to build tools for repeatable data science tasks that will accelerate and automate data scientist workflows
• Ability to mine and analyze data from various sources to solve clients problems within multiple domains like marketing, HR, supply chain, operations, sales etc
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Coding knowledge and experience with several languages: C, C++, Java,
• JavaScript, etc.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, tableau, power BI, looker etc.

Preferred Technical and Professional Experience

• Experience with open-source distributed data processing & ML frameworks
• Experience working in a Linux environment
• Experience working within a development team setup which is building product/services
• Experience with presenting complex data science processes/information to non-data scientists
• Experience with Information Retrieval and relevant tools such as Lucene, Elasticsearch, Solr
• Prioritization skills; ability to manage ad-hoc requests in parallel with ongoing projects
• Strong experience in both classical ML modeling approaches and Deep learning based model approaches
• Data analysis, reporting, visualization expertise and experience with tools such as Tableau, Alteryx, Python and R at scale
• Good NLP knowledge and cloud experience preferred
• Passion, Drive and Can-do attitude
• Good communication skills
• Willingness to thrive in ambiguous environments