Data Scientist

As a Data Scientist, you solve complex challenges and identify new opportunities using a combination of analytical expertise, business acumen, strategic thinking, and project and relationship management skills.

RESPONSIBILITIES:

  • Integrate and mine large data sets, connecting data from disparate sources to identify insights and patterns using predictive and prescriptive analytics, and machine learning techniques
  • Conduct intermediate and advanced statistical analysis, such as linear regression, ANOVA, time-series analysis, classification models, neural networks, decision trees, as well as analysis of unstructured data (e.g., social media listening, digital footprints, speech analytics)
  • Conduct research and prototyping innovations; data and requirements gathering; solution scoping and architecture; consulting clients and client facing teams on advanced statistical and machine learning problems
  • Prepare and present written and verbal reports, findings, and presentations to key stakeholders, distilling complex statistical information into easy-to-understand business language. Ability to deliver AIML based solutions around a host of domains and problems
  • Apply knowledge of U.S. businesses and corporate groups and relevant industry knowledge to analysis and insights
  • Manage project budgets and timelines, ensuring times and on-budget completion

QUALIFICATIONS:

  • Proficiency in SQL and statistical tools like R/Python
  • Ability to discover effective solutions to complex problems. Strong skills in data-structures and algorithms.
  • Experience of working on a project end-to-end: problem scoping, data gathering, EDA, modeling, insights, and visualizations
  • Problem-solving: Ability to break the problem into small problems and think of relevant techniques which can be explored & used to cater to those
  • Intermediate to advanced knowledge of machine learning, probability theory, statistics, and algorithms. You will be required to discuss and use various algorithms and approaches on a daily basis.
  • We use regression, Bayesian methods, tree-based learners, SVM, RF, XGBOOST, time series modeling, dimensionality reduction, SEM, GLM, GLMM, clustering etc., on a regular basis.
  • Excellent communication, organizational, and analytical skills. Proven ability to collaborate with internal stakeholders throughout complex projects

Good to Have: 

  • Experience in one of the upcoming technologies like deep learning, NLP, image processing, recommender systems
  • The experience of working in on one or more domains:
  • CPG: pricing and promotion analytics, marketing analytics, trade promotions, supply chain management
  • BFSI: cross-sell, up-sell, campaign analytics, treasury analytics, fraud detection
  • Healthcare: medical adherence, medical risk profiling, EHR data, fraud-waste-abuse
  • Experience in working with Linux computing environment and use of command line tools like sed/awk
  • Grasp at databases including RDBMS, NoSQL, MongoDB etc.