Responsibilities & Key Deliverables

Senior Data Scienstist/Analyst:
a) Use descriptive analysis and predictive modeling to increase and optimize customer experiences, revenue generation, campaign optimization and other business outcomes
d) End-to-end execution of the data science process, from understanding business requirements, data discovery and extraction, model development and evaluation
e) Responsible for managing & delivering the project e.g. Customer Service Retention, Customer Segmentation, Dealer profitability , Dealer Service Adherence etc .

Managing and Driving Data Maturity:
a) Working closely with Auto Data Science team ,  create  data lakes across the customer care  breadth of the organisation 
b) Mine and analyze data from established  databases to drive optimization and business strategies.

Business Engagement: 
a) Ability to interpret complex business requirements and translating them into analytical problems to deliver high value outputs
b) Solid background in the fundamentals of formulation of problem statement, system modeling and machine learning for solving the business problems
c) Client expectation Management, Project Scope, Delivery and Risk management

Driving analytics & Insighting Maturity:
a) Communication of insights that can guide actionable results through impactful insighting, story telling, data visualisation
b) Working closely with the businesses to identify and solve problems using internal and external (consumer) data, across Auto customer care 
c) Cost savings identification through focused interventions on enhancing the algorithms and data maturity through different analytics tools & build strong engagement, analytical rigor and governance framework to deliver results.

Experience

5-10 years of work experience post Masters. Must in the area of advanced Data analytics, machine leraning and artificial intelligene in customer facing domain-Sales and Service , Customer Care, Customer experience

Industry Preferred

Large Business Groups / Auto Manufacturing / Conglomerates / Specialized analytics firms  / Management Consulting Firms. 

Qualifications

Bachelors in Statistics/ Engineering + Masters in Statistics / Data Sciences / Information Management / Computer Science or MBA (Tier 1 Institutes)

Skills & Knowledge

1)  Experience in statistical modelling, machine learning, data mining, unstructured data analytics and natural language processing. Experience in working on big data platforms , Cloud based analytics pltaforms from Google/AWS/Azure 
2) Expertise in advanced machine learning techniques such as Clustering, Regression/Classification, Bayesian optimization, Neural Network, Topic Modeling , Nonparametric Methods, Multivariate Statistics, K-NN, Naïve Bayes, SVM, Time Series Analysis, Random forest, Popular Deep Learning architectures 
3) Expert in data Analysis and Data science and modelling techniques- Posesses a deep understanding of how these can be leveraged to solve business problems
4) Handson R, Python, SQL , R Shiny/Dash and Knowledge of  Qlikview/QlikSense/Tableau etc.
5)  Cross- functional knowledge of domains like sales &  services in Automotive 
6)  Interpersonal working skills (Stakeholder Management essential)