Data Scientist with Bachelor’s Degree in Computer Science, Computer Information Systems, Information Technology, or a combination of education and experience equating to the U.S. equivalent of a Bachelor’s degree in one of the aforementioned subjects.

Job Duties and Responsibilities:

• Work with cross-functional teams in the organization to identify opportunities for leveraging company data to create and drive business solutions.
• Develop scalable statistical, machine learning, or mathematical solutions for complex business problems.
• Perform analytical studies on structured and unstructured data, use statistical techniques and hypothesis testing to validate findings, and generate actionable recommendations.
• Build and evaluate classical ML models (Linear Regression, Logistic Regression, Random Forests) and Deep Learning based models (BERT, RoBERTa, ELMo, etc.) built using frameworks like Tensorflow and Pytorch for NLP applications.
• Define the end-to-end solution architecture for large-scale technology products and deep technical products in distributed processing, real-time and scalable systems.
• Architect, Design and Develop Big Data streaming applications to use high performance and highly available systems.
• Define Technology/Big Data strategy and roadmap for client accounts, and guides implementation of that strategy within projects.
• Drive excellent management skills to deliver complex projects, including effort/time estimation, to build detailed work breakdown structure (WBS), to manage critical path, and to use PM tools and Platforms.
• Build Scalable Client engagement level processes for faster turnaround and higher accuracy.
• Run regular Project reviews and Audits to ensure that projects are being executed within the guardrails agreed by all Stakeholders.
• Manage the Client Stakeholders and their expectations with a regular cadence of weekly meetings and status updates.

Technologies / Environment involved:

• Distributed storage: AWS Cloud Storage (S3), Google Cloud (GCP)
• Database management: Mongo DB
• Machine learning: TensorFlow, Keras, Pytorch, Numpy, Pandas, Scikit-learn, SpaCy,NLTK, Gensim, HuggingFace, FAIRSEQ, OpenCV.
• Programming Languages: Python, C++, MATLAB
• DevOps Tools: Git, Bitbucket