Senior, Data Analyst

Walmart•Bentonville, AR

3d•$113,589 - $155,000

About The Position

What you'll do... Position: Senior, Data Analyst Job Location: 805 SE Moberly Ln, Bentonville, AR 72712 Duties: Tech. Problem Formulation: 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 problem. Share use cases and give examples to demonstrate how method would solve business problem. Demonstrate up-to-date expertise and apply this to development, execution, and improvement of action plans by providing expert advice and guidance to others in application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales. Understanding Business Context: 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 aligns to overall business strategy and develops domain specific artifact. Serve as interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Provides and supports implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities. Data Source Identification: Support understanding of priority order of requirements and service level agreements. Help identify most suitable source for data that is fit for purpose. Perform initial data quality checks on extracted data. Data Visualization: Generate appropriate graphical representations of data and model outcomes. Understand customer requirements to design appropriate data representation for multiple data sets. Work with User Experience designers and User Interface engineers as required to build front end applications. Present to and influences team and business audience using appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance and leverage rational arguments. Guide and mentor junior associates on story types, structures, and techniques based on context. Data Quality Management: Promote and educate 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 leads data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data. Determine user accessibility and remove or restrict user access as needed. Interpret company and regulatory policies on data. Educate others on data governance processes, practices, policies, and guidelines. Exploratory Data Analysis: 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 planning, design and implementation of exploratory data analysis research projects.

Requirements

Bachelor's degree or the equivalent in Business, Engineering, Statistics, Economics, Analytics, Mathematics, or related field plus 2 years of experience in data analysis, data science, or related experience; Master's degree or the equivalent in Business, Engineering, Statistics, Economics, Analytics, Mathematics, or related field; OR 4 years of experience in data analysis, data science, or related experience.
Must have experience with: Relational database architecture and concepts to handle/store data effectively (SQL server, Oracle DB, MySQL, NoSQL, PostgreSQL); Multiple advanced data visualization tools (for example, Python, R libraries, GGplot, Matplotlib, Ploty, Tableau, Power BI etc.); Conducting statistical analysis (such as hypothesis tests, confidence intervals) and building basic statistical models using relevant packages/software suites (excel, SPSS, Minitab, etc.); Scripting and automation tools for creating operational efficiencies within the entire data architecture (Python, PowerShell, batch scripts); Creating Data pipeline with ETL tools including steps from data acquisition and transformations to storage to access (Tableau Prep, SQL Server Integration Services); Statistical techniques (for example, mean, mode, median, variance, standard deviation, correlation, and sorting and grouping); SQL development including complex queries, stored procedures, and user defined functions; Understanding forecasting concepts, algorithms, models, and tools; Discovering in Data (KDD) tools, applications, or scripting languages such as SQL, Oracle, Apache Mahout, MS Excel, Python; Considering data, analytics, stakeholder inputs, and different parts of the business when making plans; Understanding stakeholder needs, building meaningful relationships, setting up expectations, and delivering solutions within deadlines; Creating detailed project roadmaps that identify stakeholders, establish deliverables, outline timelines and communication plans; Data discovery tools to write queries and analyze data to identify patterns, trends, outliers, and correlations (SQL, Tableau Prep, Excel); Utilizing problem solving skills to troubleshoot technical issues within solutions; Establishing proper communication process to stakeholders about the resolution timelines; and Building a frameworks and models end-to-end with metrics to track/trend Return on Investment (ROI).
Employer will accept any amount of experience with the required skills.

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 problem.
Share use cases and give examples to demonstrate how method would solve 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 aligns to overall business strategy and develops domain specific artifact.
Serve as interpreter and conduit to connect business needs with tangible solutions and results.
Identify and recommend relevant business insights pertaining to their area of work.
Provides and supports implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.
Support understanding of priority order of requirements and service level agreements.
Help identify 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.
Work with User Experience designers and User Interface engineers as required to build front end applications.
Present to and influences team and business audience using appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding.
Customize communication style based on stakeholder under guidance and leverage rational arguments.
Guide and mentor junior associates on story types, structures, and techniques based on context.
Promote and educate 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 leads data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data.
Determine user accessibility and remove or restrict 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 planning, design and implementation of exploratory data analysis research projects.