Sr. Data Scientist

Designation : - Sr. Data Scientist

Experience : 4+ Yrs

Location Hyderabad (Hybrid)

Key Responsibilities

• Design, develop, and deploy AI/ML models for financial forecasting and business analytics.
• Build and optimize time series models (forecasting, trend analysis, anomaly detection) using large-scale datasets on Databricks.
• Develop custom AI tools to summarize business problems, define solution approaches, and present insights in a structured manner.
• Work on end-to-end AI solutions, from data ingestion and feature engineering to model deployment and monitoring.
• Design and work within multi-agent AI environments, enabling agents to collaborate for complex problem-solving.
• Collaborate with business, data, and engineering teams to translate requirements into scalable AI solutions.
• Ensure models meet performance, scalability, and governance standards.
• Document solutions, assumptions, and outcomes for both technical and non-technical stakeholders.
• Lead delivery of large-scale projects by breaking down work into well-defined tasks, allocating them efficiently across team members, and ensuring timely, high-quality execution (acting as a delivery foreman for the team).
• Oversee, mentor, and coach junior team members, providing technical guidance, reviewing deliverables, and ensuring skill development while maintaining overall team productivity and standards.
  

Required Skills & Experience

• Strong expertise in AI/ML concepts, including supervised and unsupervised learning.
• Hands-on experience in financial forecasting and time series analysis.
• Proven experience with Databricks, MLflow, and data processing.
• Experience building custom AI tools or frameworks tailored to specific business problems.
• Ability to summarize complex problems and solutions clearly and concisely.
• Exposure to or hands-on experience in multi-agent AI architectures.
• Proficiency in Python, ML libraries (scikit-learn, statsmodels, PyTorch/TensorFlow).
• Strong communication and stakeholder management skills.
  

Good to Have

• Experience with LLMs, prompt engineering, or agent-based frameworks.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Experience in MLOps, model monitoring, and governance.