Data Scientist

• Collaborate with stakeholders across the organization to identify opportunities for data - driven solutions.
• Mine and analyze data from company databases to optimize processes and business strategies.
• Evaluate the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to datasets.
• Utilize predictive modeling to enhance customer experiences, revenue generation, and other business outcomes.
• Establish and implement an A/B testing framework to assess model quality.
• Partner with functional teams to implement models and monitor their impact.
• Develop processes and tools to monitor model performance and data accuracy.

• Masters or PhD degree in Statistics, Mathematics, Computer Science, or a related quantitative field.
• 5-7 years of experience in data manipulation, statistical modeling, and data analysis.
• Strong problem-solving skills with a focus on product development.
• Proficiency in statistical computer languages (e.g., R, Python) for data manipulation and analysis.
• Experience in data architecture design and implementation.
• Comprehensive knowledge of machine learning techniques (e.g., clustering, decision tree learning, artificial neural networks) and their practical applications.
• Familiarity with advanced statistical concepts (e.g., regression, distribution properties, statistical tests).
• Excellent written and verbal communication skills for effective collaboration across teams.
• A passion for exploring new technologies and techniques.

Preferred Skills and Experience:

• Coding knowledge and experience in multiple languages (e.g., C, C++, Java, Python).
• Expertise in statistical and data mining techniques (e.g., GLM/Regression, Random Forest, Boosting, Trees).
• Experience querying databases and using statistical computer languages (e.g., R, Python).
• Familiarity with web services.
• Experience developing and applying advanced machine learning algorithms (e.g., regression, simulation, modeling, clustering).
• Experience analyzing data from third-party providers (e.g., Google Analytics, Site Catalyst).
• Knowledge of distributed data/computing tools (e.g., Map/Reduce, Hadoop, Hive, Spark).
• Experience working in a cloud platform Azure, GCP, AWS and their datawarehouse technologies BigQuery, Snyapse etc
• Knowledge/Experience with Snorkel AI is a strong plus