Data Science Analyst

at  Home Depot THD

TRAVEL REQUIREMENTS:

• No travel required.

PHYSICAL REQUIREMENTS:

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

MINIMUM QUALIFICATIONS:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.
• Proven experience with data mining and data analysis

PREFERRED QUALIFICATIONS:

• Working knowledge of Microsoft Office Suite
• Working knowledge of Tableau
• Working knowledge of presentation software (e.g., Microsoft PowerPoint)
• Master’s degree in a quantitative field (Analytics, Finance, Information Systems, etc.) or equivalent work experience
• 2-4 years of relevant work experience
• Working knowledge of Microsoft Excel and Power Point
• Experience in a modern scripting language (preferably Python)
• Experience running queries against data (preferably with Google BigQuery or SQL)
• Experience with data visualization software (preferably Tableau)
• Exposure to statistics, predictive modeling and other data science methodologies

MINIMUM EDUCATION:

• The knowledge, skills and abilities typically acquired through the completion of a master’s degree program or equivalent degree in a field of study related to the job.

PREFERRED EDUCATION:

• No additional education

PREFERRED YEARS OF WORK EXPERIENCE:

• No additional years of experience

MINIMUM LEADERSHIP EXPERIENCE:

• None

PREFERRED LEADERSHIP EXPERIENCE:

• None

POSITION PURPOSE:

The Data Science Analyst is responsible for data analytics that support the company’s strategic objectives and contribute to the efficiency of their data science team. This role is very collaborative, working with a variety data science roles and business functions to design and implement data analysis, tools and reporting capabilities. Another area of responsibility is the cleansing, validation, and maintenance of data sources.
As a Data Science Analyst, you will leverage your data analytics skills to translate business questions into actionable insights, support ongoing data needs, design tools to facilitate data-driven decisions and deliver high quality analytical solutions. This requires effective communication skills as well as continuous learning and development.

KEY RESPONSIBILITIES:

• 70% Data Analytics - Collaborate with business stakeholders, data scientists, and business analysts to deliver high quality analytics solutions; Determine best method to gather, model, manipulate and present data; Interpret and translate results from complex analysis into understandable and relevant insights; Perform data analytics for a variety of business problems and opportunities; Apply a wide variety of database applications and analytical tools, including SQL, Google Cloud Big Query and Python; Evaluate, process, analyze and interpret statistical data
• 20% Management of Data - Collaborate with other analysts, data scientists and business partners to explore new sources of data; Cleanse, validate and test data; Standardize and maintain data sources used by the team; Gather, model and manipulate existing data using best practice methodologies
• 10% Technical Learning - Keep up to date on industry trends, best practices and emerging methodologies; Continually develop skills and expertise in data analytics concepts and methodologies; Develop basic data science knowledge through self-learning initiatives and collaboration with team members