Job Location: Hyderābād
Overview:
Skills
Skills
This role will lead technical development within Artificial Intelligence/Machine Learning for PBNA Advanced Analytics. This will include design, implement, and maintain digital solutions for PBNA sector. The role is responsible for:
Set up and manage our AI development and facilitate production infrastructure.
Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
Build data ingest and data transformation infrastructure.
Identify transfer learning opportunities and new training datasets.
Build AI models from scratch and help product managers and stakeholders understand results.
Deploy AI models into production.
Create APIs and help business customers put results of your AI models into operations.
Keep current of latest AI research relevant to PBNA business domain.
Technical subject matter expert for Advanced Analytics and digital solution (AI, ML, Advanced Analytics)
Responsibilities:
Develop proof-of-concept demos in a SAFe Agile team
Identify transfer learning opportunities and new training datasets.
Build and deploy AI models for PBNA
Assess new capabilities within AI/ML, shape business demand to leverage digital capabilities
Develop automation for repeatedly refreshing analysis and generating insights
Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives
Quickly learn the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions
Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively
Manage own tasks and works with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and independently drives issues to resolution, minimizes surprise escalations
Qualifications:
(minimum/desirable)
PhD or Masters (or Bachelors from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.)
Skills
7+ years of relevant experience in Data Science. In case of PhD, 5+ years post qualification experience.
Hands-on experience in Statistical Modelling, Machine Learning, Deep Learning and Data Mining techniques .
Experience working in Text Analytics, NLP
Extensive experience required in: Statistical and Machine Learning techniques like Regression (esp., GLM, non-linear, etc.), Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining and Natural Language Processing (NLP)
Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization techniques, Deep Learning techniques on structured and unstructured data, Recommender Systems (content and collaborative filtering), etc.
Tools and Packages: SAS, R, Python, SQL. Exposure to dashboard or web-apps building using Qliksense, R-Shiny, Flask, etc. would be added advantage. Exposure to Azure
Experience building AI models in platforms such as Keras, TensorFlow, or Theano.
Experience in managing teams and leadership skills
Overview (Secondary Language):
This role will lead technical development within Artificial Intelligence/Machine Learning for PBNA Advanced Analytics. This will include design, implement, and maintain digital solutions for PBNA sector. The role is responsible for:
Set up and manage our AI development and facilitate production infrastructure.
Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
Build data ingest and data transformation infrastructure.
Identify transfer learning opportunities and new training datasets.
Build AI models from scratch and help product managers and stakeholders understand results.
Deploy AI models into production.
Create APIs and help business customers put results of your AI models into operations.
Keep current of latest AI research relevant to PBNA business domain.
Technical subject matter expert for Advanced Analytics and digital solution (AI, ML, Advanced Analytics)
Develop proof-of-concept demos in a SAFe Agile team
Identify transfer learning opportunities and new training datasets.
Build and deploy AI models for PBNA
Assess new capabilities within AI/ML, shape business demand to leverage digital capabilities
Develop automation for repeatedly refreshing analysis and generating insights
Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives
Quickly learn the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions
Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively
Manage own tasks and works with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and independently drives issues to resolution, minimizes surprise escalations
Responsibilities (Secondary Language):
Develop proof-of-concept demos in a SAFe Agile team
Identify transfer learning opportunities and new training datasets.
Build and deploy AI models for PBNA
Assess new capabilities within AI/ML, shape business demand to leverage digital capabilities
Develop automation for repeatedly refreshing analysis and generating insights
Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives
Quickly learn the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions
Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively
Manage own tasks and works with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and independently drives issues to resolution, minimizes surprise escalations
Qualifications (Secondary Language):
(minimum/desirable)
PhD or Masters (or Bachelors from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.)
Skills
7+ years of relevant experience in Data Science. In case of PhD, 5+ years post qualification experience.
Hands-on experience in Statistical Modelling, Machine Learning, Deep Learning and Data Mining techniques .
Experience working in Text Analytics, NLP
Extensive experience required in: Statistical and Machine Learning techniques like Regression (esp., GLM, non-linear, etc.), Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining and Natural Language Processing (NLP)
Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization techniques, Deep Learning techniques on structured and unstructured data, Recommender Systems (content and collaborative filtering), etc.
Tools and Packages: SAS, R, Python, SQL. Exposure to dashboard or web-apps building using Qliksense, R-Shiny, Flask, etc. would be added advantage. Exposure to Azure
Experience building AI models in platforms such as Keras, TensorFlow, or Theano.
Experience in managing teams and leadership skills
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