Lead Data Scientist

About the Role What you should have?

• Minimum 8+ years of relevant experience in data analytics.
• Experience in leading and executing multiple data science projects in the past Client handling experience Qualification in statistics or mathematics.
• Any data science certifications good understanding on ML & DL algorithms and frameworks (Scikit-learn, NLTK, Gensim, OpenCV, Tensorflow/Keras/PyTorch/H2Oetc.)
• Should have worked on diverse projects related to predictive analytics (supervised & unsupervised), prescriptive analytics (optimization).
• Machine Learning, Deep Learning, NLP and computer vision.
• Well versed with data science methodologies and deployment frameworks.
• Good proficiency on Python/R/Tableau/Power BI Understanding of RDBMS concepts - SQL, Oracle.
• Understanding and experience of data analytics solution delivery (end to end).
• Strong business acumen Willing to work in a challenging environment.

• Push the frontiers of what is possible in the area of machine learning to create new Incubation.
• Explore, understand, and implement the most recent algorithms and approaches for supervised and unsupervised machine learning and deep learning.
• Comfortably handle multi-terabyte data sets in scale-up and scale-out environments.
• Understand business processes that create and consume data to be able to select the best approaches, evaluate their performance, and assess business relevance.
• Create excellence both in terms of results quality and system scalability through continuous evaluation, analysis, and refinement of the system implementation.
• Communicating the relevance of implemented systems and achieving results in a visual and consistent way.
• Work closely with the team (product owner, designers, and other developers) and customers to holistically understand business and user requirements and derive adequate application development concepts.
• Performing quality assurance tasks.
• Working together with partners and customers Solve complex integration issues.
• Ability to work in global teams with different time zones.
• Immerse yourself quickly in new topics, terminology, and development tasks.