Job Description

Role and Responsibilities:

Business/Department/Objectives: 

  • The Data Sciences team is a global capability team which has the mandate to accelerate client's journey towards being future ready.
  • The Key objectives are
    • Build strong capabilities in Big Data, Machine Learning, Digital & FinTech to solve key business challenges
    • Continuously watch and learn from evolving trends
    • Be forward compatible - explore new problem solving methods

Core Responsibilities: 

  • Develop new Solutions that have high impact on revenue, expense management or customer experience
  • Use advanced Platforms (Big Data) and capabilities (Machine Learning) to improve ability to engage with customers
  • Developing Strong capabilities in Big Data, Machine Learning and Pattern mining : Build solutions that improve customer targeting- like personalized offers (Recommender systems) , Pricing/Product optimization, Journey mapping, Customer Acquisitions – Digital/Clickstream based real time offers and Channel management
  • Industrialization of Big Data and Machine Learning industrializing best practices across markets to ensure scaled deployment of solutions with strong business demand
  • Thought Leadership: Working with the site leadership and help define the agenda for Next Generation analytics (Big Data and machine learning)
  • Organizational Development: Institutionalize analytic next gen learnings across the site. Develop
  • Consulting: Advise businesses on new ways to solve business problems, inform them of industry practices that can improve business metrics
  • Relationship Management and Communication: Effectively communicate strategic considerations with team, partners and senior management

Day-to-Day Responsibilities: 

  • Collaborate with business teams to understand the challenges and innovatively come up with solutions to meet their requirements
  • Provide technical leadership and subject matter expertise on machine learning and big data to Decision Management globally
  • POC Execution: Work on multiple project/unstructured problems businesses are facing across markets, look at providing solutions that go beyond traditional methods – Using advanced technologies and new data sources
  • Institutionalize the domain knowledge by producing patentable solutions for the organization
  • Research and Development: Keep abreast of the latest developments in the analytic space across industries for potential uses. Invest time in researching the applicability of such solutions within the client
  • Talent Development: Supporting in training the resources and getting them future ready
  • Liaison with the Infrastructure and platforms team to define the tools and platforms required by the center for next generation analytics

 

Individual Contributor (IC)/Managerial: Individual/Small Team

 

Key Deliverables: 

  • Signification exposure and proven ability in Deep learning, Natural Language processing and Understanding (NLP/NLU), Large Scale Machine Learning, Distributed systems for Machine learning
  • Experienced in developing and deploying solutions in the space of machine learning in real-time platforms
  • Proven problem solving skills in industrial settings – Ability to convert open ended business problems into analytical problems and developing solutions for them
  • Competent programming aptitude with excellent computation and data mining skills – Competence in  R, Python, SAS, SPSS, Java and Spark/Scala
  • Experience in
    • Big Data/HADOOP
    • Text Analytics – Ability to synthesize unstructured data and find actionable themes/insights
    • Pattern Mining/Detection
    • Machine Learning Classification Algorithms
    • Deep Learning and Neural Networks
    • Ability to translate and articulate technical thoughts and ideas to a larger audience including influencing skills with peers and senior management
    • Self-motivated to continuously upgrade one’s domain knowledge, keep abreast of latest developments in the field and evaluate its application in the business area on a consistent basis

Percentage of Travel: 

  • No                                 
  • Yes, 10% of the Time      
  • Yes, 25% of the Time 
  • Yes, 50% of the Time 
  • Yes, 75% of the Time      
  • Yes, 100% of the Time

Relocation: Yes

Education: 

  • Required
    • Field of post-graduation – Computer Science, Mathematics, Operations Research, Statistics, Econometrics, Management Science and related fields. Could be any graduate degree holder.
    • Strong academic record and publications in reputed journals or conferences. 

Experience: 

  • Required
    • 6-10 years of experience in the field of advanced quantitative techniques, data sciences and large scale machine learning  while working for leading global academic institutes or corporate innovation research labs or analytics organizations of large corporates or in consulting companies in analytics roles 

Skills

  • Required
    • Signification exposure and proven ability in Deep learning, Natural Language processing and Understanding (NLP/NLU), Large Scale Machine Learning, Distributed systems for Machine learning.
    • Expertise Required
    • Big Data/HADOOP – HIVE/PIG , Java and Spark/Scala
    • Text Analytics – Ability to synthesize unstructured data and find actionable themes/insights – exposure to SPSS/Python/R
    • Pattern Mining/Detection
    • Exposure to Machine Learning Algorithms 

Other

  • Required
    • Field of post-graduation – Computer Science, Mathematics, Operations Research, Statistics, Econometrics, Management Science and related fields. Could be any graduate degree holder

 Contact Details

Name:   Hiren Sulakhe

Email :   hiren.sulakhe@rangaminfotech.com

Phone:   722-704-3706