Senior Data Scientist

Key Responsibilities

• Design, Develop and Deploy ML powered products and pipelines
• Play a central role in all stages of the data science project life cycle, including:
• Identification of suitable data science project opportunities
• Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
• Evaluation/interpretation of results and presentation to business leaders
• Performing exploratory data analysis, proof-of-concept modelling, model benchmarking and setup model validation experiments
• Training large models both for experimentation and production
• Develop production ready pipelines for enterprise scale projects
• Perform code reviews & optimization for your projects and team
• Spearhead deployment and model scaling strategies
• Stakeholder management and representing the team in front of our leadership
• Leading and mentoring by example including project scrums

What Were Looking For:

• 3 - 7 years of professional experience in Data Science domain
• Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.)
• Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures
• Expertise in probabilistic machine learning model for classification, regression & clustering
• Strong experience in feature engineering, data preprocessing, and building machine learning models for large datasets.
• Exposure to Information Retrieval, Web scraping and Data Extraction at scale
• OOP Design patterns, Test-Driven Development and Enterprise System design
• SQL (any variant, bonus if this is a big data variant)
• Linux OS (e.g. bash toolset and other utilities)
• Version control system experience with Git, GitHub, or Azure DevOps.
• Problem-solving and debugging skills
• Software craftsmanship, adherence to Agile principles and taking pride in writing good code
• Techniques to communicate change to non-technical people

Nice to have

• Prior work to show on Github, Kaggle, StackOverflow etc.
• Cloud expertise (AWS and GCP preferably)
• Expertise in deploying machine learning models in cloud environments
• Familiarity in working with LLMs