Data Scientist

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Job Role: Data Scientist

Client Location: Hyderabad

Shift : 6 PM 3 AM IST

Joining: Earlier the best

Employment: Full-Time

Experience : 6+ yrs

Responsibilities:

• The Data Scientist for Information Management & Analytics identifies and capitalizes on opportunities to improve business performance and improve customer experience through developing algorithms that provide real-time business recommendations for business decisions and real-time recommendations for customers using web/mobile platforms.
• Primary areas of focus will be Digital Analytics and Owner Satisfaction, with additional areas of focus include Pricing, Inventory Management, Sales Efficiency, Marketing and Portfolio performance.
• This role requires integration and collaboration with the ML Ops team, Operational Reporting team and IT partners.

Key Responsibilities:

• Design and develop new algorithms to support real-time recommender systems
• Work, as directed, on developing analytical models to support strategic management decision making
• Maintain and enhance existing forecasting models; build new models to incorporate user feedback and google analytics data
• Work on ad-hoc analysis and handle data requests from business stakeholders
• Provide support for existing analytical processes and meet stakeholders' service expectations
• Maintain asset bundles and API endpoints for production-level models
• Develop and maintain good documentation of code and processes. Assist in writing user manuals, as needed
• Prepare commentary around findings and implications of analysis
• Bridge operational analytics to financial impacts, participate in project-based initiatives and perform other duties as assigned

Key Skills:

• Proficiency in programming languages such as Python, R, and SQL for data manipulation and model development.
• Strong understanding of machine learning algorithms, including recommender systems, forecasting models, and predictive analytics.
• Experience with data visualization tools (e.g. Power BI or similar) for presenting insights.
• Familiarity with cloud platforms and ML Ops practices for deploying and maintaining models in production.
• Familiarity with Code Management and Version Control(Git, ADO, etc)
• Knowledge of API development and integration for real-time model consumption.
• Expertise in statistical modeling, hypothesis testing, and experimental design.
• Ability to work with large datasets, perform data cleaning, and ensure data quality.
• Experience with digital analytics tools (e.g., Google Analytics) and customer behavior analysis.
• Excellent written and verbal communication skills for preparing commentary and documentation.
• Experience with Databricks asset bundles and ADO pipelines