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Tier-1 brand, mid-level ML role, metro location, and broad skillset drive high applicant competition.
High because advanced ML, deep learning, and big data skills are domain-specific and less transferable.
Requires postgraduate degree plus extensive mandatory ML, big data, cloud, and programming expertise.
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Lead and manage data science and engineering components of AI projects across multiple business units.
Set strategic direction for data identification, collection, and qualification activities to support analytics efforts.
Develop and implement mathematical, AI models/algorithms and best practices for data science lifecycle including evaluation of new analytical tools.
Experience Required: Extensive professional experience applying statistics, data mining, machine learning, and deep learning techniques including handling structured, unstructured, and streaming data.
Must have strong programming skills in Python, Java, C, or C++ and expertise with Big Data platforms like Spark and cloud platforms such as AWS.
Master’s degree or PhD in quantitative fields such as Computer Science, Economics, Engineering, Statistics, Mathematics, Finance, or Operations Research.
Experience working on relational, NoSQL, and graph databases; exposure to deep learning frameworks like TensorFlow, Theano, Torch, or Caffe preferred.
Demonstrated strategic leadership in managing complex AI and data analytics projects across diverse business domains.
Proven ability to self-direct work in ambiguous scenarios and collaborate with multiple senior stakeholders and cross-functional teams.
Experience with cutting-edge advanced analytics, predictive modeling, AI applications and familiarity with implementing machine learning solutions including NLP, NLU, computer vision and RPA.