Manager – Yield Foundation

Manager – Yield Foundation

Requirements

• Master’s degree or equivalent in Data Science, Machine Learning, Computer Science, Mathematics, Operations Research, Economics, Statistics, Analytics (any), or related area; OR Bachelor’s degree or equivalent in Data Science, Machine Learning, Computer Science, Mathematics, Operations Research, Economics, Statistics, Analytics (any), or related area and 2 years of experience in yield management, pricing strategy, business analysis, business planning, database management, optimization, or related area.
• Experience performing data extraction and analytics using SQL queries across BigQuery, Teradata, Microsoft Azure, and Databricks.
• Experience designing, deploying, and maintaining executive level self-serve and automated dashboards using Tableau and Power BI.
• Experience developing and optimizing end-to-end ETL pipelines by aggregating and joining data using Python, SQL, Dataproc, Airflow, R, and VBA.
• Experience working on REST API calls utilizing Python and R to fetch data from across the web for data analysis and modeling.
• Experience with strategy and analytics to derive actionable insights on business health from big data and report to leadership.
• Experience performing statistical analysis including regression, hypothesis testing, ML modeling, and forecasting.
• Experience fetching web analytics data and creating analytical reports from web platforms including social media, google analytics, and adobe analytics.

Responsibilities

• Translate/co-own business problems within one’s discipline to data related or mathematical solutions.
• Identify appropriate methods/tools to be leveraged to provide a solution for the problem.
• Share use cases and gives examples to demonstrate how the method would solve the business problem.
• Provide recommendations to business stakeholders to solve complex business issues.
• Develop business cases for projects with a projected return on investment or cost savings.
• Translate business requirements into projects, activities, and tasks and align to overall business strategy and develops domain specific artifact.
• Serve as an interpreter and conduit to connect business needs with tangible solutions and results.
• Identify and recommend relevant business insights pertaining to their area of work.
• Support the understanding of the priority order of requirements and service level agreements.
• Help identify the most suitable source for data that is fit for purpose.
• Perform initial data quality checks on extracted data.
• Generate appropriate graphical representations of data and model outcomes.
• Understand customer requirements to design appropriate data representation for multiple data sets.
• Present to and influence the team and business audience using the appropriate data visualization frameworks and convey clear messages through business and stakeholder understanding.
• Customize communication style based on stakeholder under guidance, and leverages rational arguments.
• Guide and mentor junior associates on story types, structures, and techniques based on context.
• Promote and educates others on data quality awareness.
• Profile, analyze, and assess data quality.
• Test and validate data quality requirements.
• Continuously measure and monitor data quality.
• Deliver against data quality service level agreements.
• Manage operational Data Quality Management procedures.
• Manage data quality issues and lead data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data.
• Determine user accessibility and removes or restricts user access as needed.
• Interpret company and regulatory policies on data.
• Educate others on data governance processes, practices, policies, and guidelines.
• Collect and tabulate data and evaluate results to determine accuracy, validity, and applicability.
• Support the identification and application of statistical techniques based on requirements.
• Apply suitable technique under direction from leadership.
• Assist in the planning, design and implementation of an exploratory data analysis research projects.
• Understand existing statistical models and identify and recommend statistical models based on hypothesis.
• Use advanced Knowledge in Data Discovery tools to write queries and analyze data to identify patterns, trends, outliers, and correlations.
• Conduct statistical analysis (for example hypothesis tests, confidence intervals) and build basic statistical models using relevant packages/software suites.
• Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.
• Recognize and adapt to differences in background, culture, language and work style, when working with others.
• Communicate with other individuals or teams to solve shared problems cooperatively.

Preferred Qualifications

• Any amount of experience with the required skills.