Business Analyst (In a Data group) (NO Data...

6-12 Month Contract /100% Remote/Business Analyst in a Data Group/$70 - $80 /Per hr The IT Business Analyst Analytics will work in conjunction with the Analytics team to develop functional technical requirements. Working closely with business stakeholders, IT and third parties the candidate will work to develop solid business requirements documents and project deliverables... Responsibilities: ??Identifying and documenting requested changes to the system in a standard BRD ??Identifying analytics needs arise in their functional area as well as issues that impact other functional teams, and working to resolve them ??Serving as a liaison between end users' workflow needs and Analytics team implementation staff ??Maintaining regular communication with Analytics team members including participating in weekly project team meetings ??Working with business units, and end users to ensure the analytics application meets the organization's business needs regarding the project deliverables ??Developing an understanding of operational needs by attending site visits and other integrated sessions ??Contributing member of a team of analysts, developers and support staff that will assist with automation activities ??Build, develop, and maintain highly collaborative working relationships with the business and IT ??Support and align efforts to meet IT and business needs ??Develop and execute test plans, provide necessary guidance to testers during QA process ??Determining required testing resources ??Managing the issue tracking process Requirements: ??Bachelor's degree, or similar technical discipline ??5+ years in data domain ??Experience working within teams ??Must be able to travel up to 20% ??Strong Analytical Skills: A business analyst focused on data science projects should have strong analytical skills to understand complex data sets, identify patterns and trends, and derive insights. They should be proficient in statistical analysis, data exploration techniques, and data visualization. ??Domain Knowledge: Possessing domain knowledge relevant to the specific industry or business area being analyzed is valuable. It enables the business analyst to understand the context, interpret data findings in a meaningful way, and provide insights that align with business objectives. ??Understanding of Data Science Concepts: While not necessarily being a data scientist themselves, a business analyst focused on data science projects should have a solid understanding of data science concepts. This includes familiarity with machine learning, predictive modeling, data preprocessing, and evaluation techniques. ??Collaboration and Communication: Effective collaboration and communication skills are crucial for a business analyst working on data science projects. They need to work closely with data scientists, subject matter experts, and stakeholders to understand project requirements, translate business needs into analytical solutions, and effectively communicate findings and recommendations. ??Data Manipulation Skills: Proficiency in data manipulation is essential. This includes skills in data cleaning, data transformation, feature engineering, and data integration to prepare data for analysis. Familiarity with tools such as SQL, Python, or R for data manipulation is beneficial. ??Problem-Solving Abilities: Data science projects often involve complex problems that require creative problem-solving skills. A business analyst should be able to break down complex problems, identify relevant variables, and propose data-driven solutions that address business challenges. ??Business Acumen: Having a strong understanding of business processes, goals, and strategies is critical. A business analyst should be able to connect data insights to business outcomes, make recommendations that align with business objectives, and drive decision-making based on data-driven insights. ??Adaptability and Continuous Learning: Data science is a rapidly evolving field, and a business analyst should possess adaptability and a willingness to learn. They should stay updated with the latest data science techniques, tools, and trends to effectively contribute to data science projects. ??Data Ethics and Privacy Awareness: With the increasing importance of data ethics and privacy, a business analyst focused on data science projects should be mindful of ethical considerations related to data usage, privacy regulations, and best practices for data handling. ??Project Management Skills: Project management skills are valuable for effectively managing data science projects. This includes skills in project planning, resource allocation, timeline management, and coordination with stakeholders to ensure successful project execution.

Cincinnati Bell Technology Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws

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