Data Scientist/Principal Consultant

(1 Opening)

Job Location – Hyderabad   |   Position – Full-Time 

People Involvement – IC, Product Development Team.

Skills (Must Haves):

10+ years of experience in analytics, preferably – 

  • 5+ years of experience in data science teams. Academic projects will not be counted. POC will not be counted. Kaggle competitions will not be counted.
  • Strong statistical background with bachelor’s or Masters in Maths, Stats.
  • Minimum 3-5 Projects in productions/development should be in production during tenure.

Primary –Statistical Modelling and Machine Learning – Full Stack development.

Secondary – Deep Learning Architectures – Machine Learning & NLP. 

Data Engineering

  • Hands on with integration with connection to, DBMS, Hadoop file structures etc. experience connecting these to visual tools.
  • Strong knowledge of social media analytics and external databases on data acquisitions.

Data Analytics 

  • Business Analytics using Tableau, Power BI, Einstein Analytics, or any Py/R library

Machine Learning

  • Only experienced production staff of 3-5 years should apply. POC work will not be applicable for this role.
  • Strong inclination of Statistics and mathematics with a focussed business acumen,
  • Supervised and Unsupervised learning algorithms.
  • Should be strong in parametric approaches and machine learning concepts.

Machine Learning Problems

    • Optimization
    • Forecasting, Univariate, and multivariate T+3 periods ahead.
    • Binary Predictions.
    • Continuous predictions.
    • Unsupervised problems.
    • NLP based predictions.
    • Sentiment Analysis.
    • Very strong statistical modelling with an outlier of EDA. 

Responsibilities:

Deliver Features as identified in respective scrums for the development products with agreed accuracy in production.

  • Successful delivery of the use cases POC’s as identified by the business requirements.
  • Train and mentor junior staff, aspiring data scientists.

Data Engineering

  • Manage the SQL data bases and converse with AWS.
  • Maintain the SQL Jobs, and analytical data marts.
  • Publish the quality reports, manage the development lifecycle with team members.

Data Analytics

  • Identify KPI’s, talk to customers, domain experts and identify the story line.
  • Build inferential charts, some common charts.
    • Box Plots
    • SQC Charts
    • Correlations
    • Advanced charts

Management

  • Manage, guide and mentor a team of juniors.
  • Stakeholder management – 20-30%
  • Client Engagement – 20-30%

Deployment

  • Work with AWS team to deploy solutions.
  • Build machine learning pipelines and deploy the model in production.
  • Train and monitor the model/feature to the implementation team structurally.
  • Enhance customer experience by minimizing the deployment time.
  • Technical capability of customizing the product as per customer need.

Tools

  • R (20%) or Python (80%), should upskill in R.
  • R Shiny Dev, Py Django or Flask or Dash + Server Management.
  • Tensor-flow, keras, framework.

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