AVP, Text Mining/NLP - Bengaluru, India - Genpact

    Genpact
    Genpact Bengaluru, India

    2 weeks ago

    Genpact background
    Description

    With a startup spirit and 1,15,000+ curious and courageous minds, we have the expertise to go deep with the world's biggest brands—and we have fun doing it We dream in digital, dare, and reinvent the ways companies work to make an impact far bigger than just our bottom line.

    We're harnessing the power of technology and humanity to create meaningful transformation that moves us forward in our pursuit of a world that works better for people.

    Now, we're calling upon the thinkers and doers, those with a natural curiosity and a hunger to keep learning, keep growing.

    People who thrive on fearlessly experimenting, seizing opportunities, and pushing boundaries to turn our vision into reality. And as you help us create a better world, we will help you build your own intellectual firepower.
    Welcome to the relentless pursuit of better.
    Inviting applications for the role of

    AVP,

    Text Mining/NLP - Data Science and Insights.

    The candidate should be PhD in Computer Science, Information systems, or Computer engineering, Systems Engineering with experience in Text Mining / Natural Language Processing (NLP) tools, Data sciences, Big Data, and algorithms.

    OrFull cycle experience desirable in at least 1 Large Scale Text Mining/NLP project from creating a business use case, Text Analytics assessment/roadmap, Technology & Analytic Solutioning, Implementation and Change Management, considerable experience in Hadoop including development in map-reduce framework.

    ResponsibilitiesThe Text Mining Scientist (TMS) is expected to play a pivotal bridging role between enterprise database teams, and business /functional resources.

    At a broad level, the TMS will leverage his/her solutioning expertise to translate the customer's business need into a techno-analytic problem and appropriately work with database teams to bring large scale text analytic solutions to fruition.

    The right candidate should have prior experience in developing text mining and NLP solutions using open-source toolsThe key responsibilities of the Text Mining Scientist are:


    • Develop transformative AI/ML solutions to address our clients' business requirements and challenges.
    • Project Delivery - This would entail successful delivery of projects involving data Pre-processing, Model Training and Evaluation, Parameter Tuning
    • Manage Stakeholder/Customer Expectations
    • Project Blue Printing and Project Documentation
    • Creating Project Plan
    • Understand and research cutting edge industrial and academic developments in AI/ML with NLP/NLU applications in diverse industries such as CPG, Finance etc.
    • Conceptualize, Design, build and develop solution algorithms which demonstrate the minimum required functionality within tight timelines
    • Interact with clients to collect, synthesize, and propose requirements and create effective analytics/text mining roadmap.
    • Work with digital development teams to integrate and transform these algorithms into production quality applications
    • Do applied research on a wide array of text analytics and machine learning projects, file patents and publish the papers
    Qualifications we seek in you

    Minimum Qualifications

    Specific Competencies – EssentialTechnology

    • Open-Source Text Mining paradigms such as NLTK, OpenNLP, OpenCalais, StanfordNLP, GATE, UIMA, Lucene, and cloud based NLU tools such as Dialog Flow, MS LUIS
    • Exposure to Statistical Toolkits such as R, Weka, S-Plus, Matlab, SAS-Text Miner
    • Strong Core Java experience in large scale product development and functional knowledge of RDBMs
    • Hands on to programming in the Hadoop ecosystem, and concepts in distributed computing
    • Very good python/R programming skills. Java programming skills a plusMethodology
    • Solutioning & Consulting experience in verticals such as BFSI, CPG, Healthcare, Insurance with experience in delivering text analytics on large structured and unstructured data.
    • A solid foundation in AI Methodologies like ML, DL, NLP, Neural Networks, Information Retrieval and Extraction, NLG, NLU
    • Exposed to concepts in Natural Language Processing & Statistics, esp., in their application such as Sentiment Analysis, Contextual NLP, Dependency Parsing, Parsing, Chunking, Summarization, etc.
    • Demonstrated ability to Conduct look-ahead client research with focus on supplementing and strengthening the client's analytics agenda with newer tools and techniques