People Analytics & Insights - Data Science Lead

People Analytics & Insights - Data Science Lead - MISSISSAUGA | Citi Careers

Responsibilities not listed.

• Master’s Degree/ Bachelor’s degree preferably in Statistics, Economics, Mathematics / B.tech in Computer science, IT
• Extensive experience in Advanced SQL (or similar language for querying relational databases)
• Advanced Python programming skills
• Experience using platforms such as Oracle, Google Cloud, Snowflake, Airflow etc.
• Experience with Big Data tools: Hadoop, Spark, Kafka
• Tableau and other data visualization tools
• Demonstrated ability to lead projects to timely delivery
• Strong analytical skills related to working with unstructured datasets
• Experience managing and working with large databases, data management, including understanding of various data structures and common methods in data transformation, data validation and audit
• Demonstrated strong collaboration skills—Analytics & Insights is a team sport.
• Ability to manage and work with structured and unstructured data with accuracy
• Ability to multitask and manage multiple research/analytics projects at the same time
• Demonstrated strong attention to detail, problem-solving, and critical thinking
• Business and HR acumen is preferred
• Adaptive to matrix work environment

• Collaborate with cross-functional teams, including data scientists, project managers, HR partners and business stakeholders, to understand data requirements and define data engineering solutions that support workforce planning goals.
• Working with the HR technology team and various other partners to build and maintain the People Analytics and Insights database.
• Lead and mentor a team of data scientists, data engineers and tableau developers.
• Applying analytical/technical expertise to translate business problems into actionable solutions.
• Develop and implement data models to support advanced analytics and machine learning applications related to workforce planning and optimization.
• Leading execution and automation of analytical and reporting projects to ensure that the outputs fulfill client requirements and expectations.
• Performing ETL tasks and data analyses (exploratory, confirmatory and/or qualitative), which include wide use of reporting frameworks and statistical models/ tests using Python, Tableau etc.
• Effectively communicate findings, ideas, and concepts to non-technical stakeholders both internally and externally.
• Staying abreast of current trends/research in data science research and technology

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