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nt opportunities in an environment that embraces your unique skills and experience.
Your Role and Responsibilities
The Data Scientist role combines deep data and analytics skills with strong business acumen to solve business problem of Cognitive Computing Solutions. The responsibilities include working with business leaders to solve business problems by understanding, preparing, and analysing data to predict emerging trends and provide recommendations to optimize business results
The data scientist is expected to have expertise of Advanced Analytics techniques that are traditionally applied to structured data, as well as deep understanding of Natural Language Processing and Machine Learning techniques such as Deep Learning and GenAI for unstructured content, so as to enable composition of holistic cognitive solutions. The candidate is expected to be well versed in one of the following areas of Natural Language Processing, Image Processing, Video Processing, Voice Processing, Q&A assistant solutions and other forms of GenAI solutions. The candidate is expected to have knowledge and/or experience in the following skills with focus on Data Science: Machine Learning, Git, Agile, SQL, Python, R, Predictive Modelling, Algorithms, Web Scraping, TensorFlow, Deep Learning, Statistics and Natural Language Processing / GenAI and Agentic AI. This will include the following:
The ideal candidate will have 7-12 years of experience in designing, GenAI, Deep Learning, ML/statistical solutions to complex business problems at scale; developing & testing modular, reusable, efficient and scalable code to implement those solutions. The skills include strong coding, statistical, mathematical, predictive modelling, and business strategy skills and will need to be able to effectively communicate orally and visually -- what all of the data means in the context of our business.
Required Technical and Professional Expertise
BTech (with 7+ years of relevant experience) or Masters (with 6+ years of relevant experience) in Operations Research, Applied Mathematics/ Statistics/ Econometrics, Electrical or Systems Engineering, Physics or similar highly quantitative field
Strong ability to transform business requirements into data science formulations and implement the solutions in an efficient and scalable fashion
Sound understanding of data science concepts, model development & performance tuning processes as well as coding, version control and CI/CD best practices
Demonstrated extensive experience in building and deploying production quality models in a live digital environment using data pipelines and ML Ops frameworks including handling model drift, retraining and version control lifecycle
Highly skilled in Python and various data science related libraries of Python including TensorFlow, Keras, Sci-Kit Lean, Pandas, Numpy and PySpark
Experience in Convolutional Neural Network / Computer Vision projects using TensorFlow, PyTorch and leveraging public / open-source libraries (VGG16, ImageNet, YOLO, OpenCV, etc) as well as ability to tweak, modify these CNN architectures when required for a specific business problem.
Demonstrated ability of scoping, executing and scaling multiple data science deliverables on their own
Must have worked in developing and deploying models using more than one cloud platform (AWS, Azure, GCP, IBM)
Ability to handle multiple projects as an individual contributor and as a lead / mentor to other team members managed directly or indirectly on a project / assignment
Excellent interpersonal and stakeholder management skills including ability to interact and present to senior stakeholders
Preferred Technical and Professional Expertise