Job Description

Responsibilities

• Responsible for overseeing the data scientists team and machine learning engineers with regular guidance
• Understand the business scenarios and provide inputs on different AI/ML Use-case prospects
• Work on complex and big data framework as part of the data science engagements
• Highly motivated and ability to work peacefully in stressed environment
• Develop ML & AI models based on structured and unstructured data with ability to combine NLP and Image processing
• Orchestrate complete workflow starting with reading the data from source to publishing model output
• Present the work to internal/external stakeholders
• Work with Pre-sales team to build the use-cases or models for customer
• Establish standards and accelerators or PoC, internally or for customers to address larger business opportunities
• Teach, lead, and counsel colleagues on new techniques or solutions
• Collaborate with data and software engineers to enable deployment of models and technologies that will scale across Navikenz customer’s ecosystem
• Provide support to data science team with high-level expertise in an open-source language (e.g., R, Python, Julia, etc.)
• Spot and evaluate emerging/cutting edge, open source, data science/machine learning libraries/big data platforms (e.g. XGBoost, H2Oai, Spark, Hadoop, etc.)
• Work on papers to publish problem solving approach with ML Models, NLP and Computer vision techniques
• Conduct research and develop prototypes for demonstrations
• Work on lab management for enabling data scientist, data engineers to work on sandbox environment and drive knowledge enhancements

Qualifications/Experience

The ideal candidate will have a Master’s degree or PhD in Statistics, Mathematics, Computer Science, Operations Research or another quantitative field, with at least 5 years of professional experience manipulating data sets and building statistical models, and familiar with the following software/tools/techniques (overall 15 years of experience):

• Proven experience in working with large datasets
• Worked on structured, semi-structured and unstructured data
• Worked on projects which includes computer vision
• Highly skilled in advanced level programming in Python using libraries like pandas, scrapy, tensorflow, scikit-learn, keras, matplotlib etc.
• Coding knowledge and experience with several languages: Python/R/Julia, Java/Javascript, REST, etc.
• Proven experience working on NLP using python libraries like NLTK, pattern, gensim, spacy, textblob etc.
• Hands on experience with developing & interpreting time series models, linear regression, logistic regression, neural network, random forest, clustering etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Databricks, H2O.ai, etc.
• Knowledge of CI/CD, version control, orchestration tools
• Experience with cloud based platforms/products – AWS, Azure, GCP, Kubeflow, AutoML etc.
• Working knowledge of visualization tools QlikView/Power BI/Tableau
• Knowledge of statistical concepts like hypothesis testing, probability distribution etc.