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Data Analyst

Spectraforce Technologies

Raleigh, NC • Remote

Other

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Job description

Job Title: Data Analyst
Assignment Duration: 4-month, possible extension
Hours: M-F 8am - 5pm EST or CST preferred
Location: Remote
Why is this role open? (Coverage, looking for perm, etc.) To complete an ongoing project
Potential to convert to FTE, If so, what rate: Possible if headcount is available
Overview of Work Environment/Client Nuances:
Potentially some interaction with the client so they will need to have excellent communication skills
Team Overview:
will work closely with H.M and team of data analysts
Resource's typical working day:
  • Data management
  • May do some vendor management
  • Some data presentation
  • Some process improvement
  • Data mining to assist operations around lab equipment maintenance
  • Some vendor management

Licenses/Certifications: n/a
Must Have Skills:
  • Extreme attention to detail
  • Great with time management and has a sense of urgency to complete tasks
  • Excellent communication skills
  • Will need to be able to "tell the story of the data"

Nice to have skills:
Experience with pharmaceutical equipment management is a huge plus
Years of Experience: 4-7 years
Education
Bachelor's degree highly preferred, will accept experience in lieu of.
Software skills:
Excel
Microsoft Office suit
Smart sheets
Interview Process:
1 round, virtual (Teams) with H.M.
About the Role:
As a client Data Analyst, you will perform basic analysis to ensure that recommendations and business conclusions are backed by thorough data research and findings.
This job is part of the Data Science & Analytics job function. They are responsible for reviewing data that supports improving effectiveness and predicting outcomes to develop business intelligence.
What You'll Do:
  • Coordinate data aggregation and curate reports using existing business intelligence and reporting applications.
  • Perform ad-hoc, strategic review of structured and unstructured data, reflecting global real estate markets and the operations of real estate assets.
  • Assist with developing data structures and pipelines to organize, collect, cleanse, and standardize information to generate insights.
  • Define basic data requirements and gather information using judgment and statistical tests.
  • Use programming and evaluation tools, including open-source programs to plan models and extract insights.
  • Apply modeling and optimization methods to improve business performance.
  • Develop ad-hoc reporting based on the review of existing data sources.
  • Exhibit rigor, judgment, and ability to present a detailed 'data story' to a business line.
  • Confirm the quality and integrity of existing data sources.
  • Collaborate with the agile development team to provide recommendations and communications on enhancing existing or new processes and programs.
  • Have some knowledge of standard principles with limited practical experience in applying them.
  • Lead by example and model behaviors that are consistent with client RISE values.
  • Impact the quality of own work.
  • Work within standardized procedures and practices to achieve objectives and meet deadlines.
  • Exchange straightforward information, ask questions, and check for understanding.

What You'll Need:
  • Bachelor's Degree preferred with up to 3 years of relevant experience. In lieu of a degree, a combination of experience and education will be considered. MCSE and CNE Certification preferred.
  • Ability to use existing procedures to solve standard problems.
  • Experience with analyzing information and standard practices to make judgments.
  • In-depth knowledge of Microsoft Office products. Examples include Word, Excel, Outlook, etc.
  • Organizational skills with a strong inquisitive mindset.

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Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Analyst?

A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.

Q: What is the career path for a Data Analyst?

A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.

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