Senior Data Scientist

1. Visualizing the scope of the project end to end * Identify the expected outcome * Figure out the data present and required for successful completion of the project * Defining the scope and effort needed for project execution * Devising monitoring frameworks

2. Stakeholder management * You should be able to communicate with business stakeholders proactively to find out their pain points and propose a data backed solution to them * Should be able to formulate the complete steps to execution of the project with clarity on timelines * Should be good with data storytelling to ensure analytical models are easy to consume for different business functions

3. Data standardization and integrity efforts * Ensuring we keep sanitizing our data sources and keep raising flags to functions who own these data sources for data issues * Ensure checks and reporting engines are in place to pick up anomalies in data pipeline

4. Project management * Ensure timely closure of projects on or before committed timelines * Step by step monitoring of Projects from whiteboarding to deployment * Ensure model monitoring and communication around unusual spikes (if any)

5. Mentoring * Mentoring junior resources on their projects * You must bring your industry experience into the project to ensure junior resources are able to correlate their work with business impact

• Proficiency in Python/R
• Pyspark and cloud tech exposure is a plus
• Expertise in SQL querying
• Product and model deployment on cloud platforms like GCP/AWS, * Qualifications preferred: PhD/Masters/Bachelors in Statistics, Engineering, Economics, Machine learning, Computer science, IT etc.

Work Experience

• Proven experience of 4+ year of relevant experience
• Other skills - Data Interpretation, Visualization, Programming
• Knowledge of underlying mathematical foundations of statistics, ML and analytics
• Experience in EDA, model development and validation
• Experience in building and evaluating algorithms and optimizing the ML models in production
• Experience in productionizing algorithms for real - time systems
• Experience in influencing product and sourcing strategies with data centric presentations
• Experiencing with statistics for statistical inferences, testing strategies, evaluating regression problems