Senior Data Scientist

Job Responsibilities

• Analyze complex data sets to identify trends, patterns, and insights that can drive business decisions.
• Design and develop predictive models, algorithms, machine learning, and artificial intelligence techniques to improve the accuracy and efficiency of analytics solutions
• Collaborate with cross-functional teams to ensure the data used is accurate, relevant, and up-to-date for analytics purposes.
• Contribute to hands-on development of data & analytics solutions.
• Deliver products and solutions in a timely, proactive, and entrepreneurial manner.
• Accelerate solution delivery using re-usable frameworks, prototypes and hackathons.
• Follow MLOps principles to ensure scalability, repeatability, and automation in the end-to end machine learning lifecycle.
• Developing and maintaining detailed technical documentation.
• Stay up-to-date on industry trends and new technologies in data science and analytics, and apply this knowledge to improve the firm's analytics capabilities

Education, Technical Skills & Other Critical Requirement

• 0-5 years of relevant experience in AI/ analytics product & solution delivery
• Bachelor’s/Master’s degree in an information technology/computer science/Statistics/ Economics or equivalent fields experience.
• Strong understanding of Machine Learning and Deep Learning concepts, with a focus on Natural Language Processing.
• Proficiency in Python programming language, with experience using libraries like PyTorch for deep learning tasks.
• Familiarity with Elastic stack (Elasticsearch, Logstash, Kibana) for data management and analysis.
• Experience in optimizing algorithms and time series forecasts.
• Knowledge of prompt engineering techniques to improve model performance.
• Ability to prototype applications using Streamlit or similar tools.
• Experience working with large and complex internal, external, structured and unstructured datasets.
• Model development and deployment in cloud; Familiarity with Github, CI/CD process, Docker, Containerization & Kubernetes.
• Strong conceptual and creative problem-solving skills
• Good written, verbal communication skills and presentation skills; engage in meaningful manner with variety of audience: business stakeholders, technology partners & practitioners, executive and senior management.
• Industry knowledge about emerging AI trends, AI tools and technologies

Preferred:

• Familiarity of new age AI and ML techniques such as GenAI, foundational models, large language models (LLMs) and applications
• Certifications in AI space such as ML Ops, AI Ops, Generative AI, Ethical AI, AI deployment in cloud
• Familiarity with agile methodologies & tools
• Prior experience in P&C Insurance Analytics
• Prior experience in Analytics consulting and services