Forvis Mazars US
Senior Consultant, Analytics
Employer: Forvis Mazars US
Overview The Analytics team transforms data into actionable insights that fuel business growth. Using advanced tools in predictive analytics, machine learning, and AI, they help organizations unlock new opportunities, reduce risk, and improve efficiency. Their proprietary cloud‑based platform delivers timely, digestible insights that enhance strategy and performance. With a strong focus on data strategy, governance, and security, they ensure data quality and compliance—empowering clients to make confident, data‑driven decisions.
Responsibilities
Engage with clients professionally and consistently to understand their needs, deliver effective solutions, and build trust.
Support client engagements throughout all phases of the project lifecycle, including implementation and support of the tools and products we build.
Support tax, audit, and other teams with insights gained from analyzing data, automating tasks, and problem‑solving.
Utilize analytical, statistical, and programming skills to collect, analyze, and interpret data sets and develop data‑driven solutions to difficult business challenges.
Create client deliverables and technical documentation that clearly details analytic procedures, outputs and insights, and key reference information.
Perform core data analytic tasks, including designing and implementing procedures to collect, transform, cleanse, normalize, and analyze data; automating reports, dashboards, and other performance tools; providing ad‑hoc analysis and presenting results in a clear manner.
Maintain and achieve high quality in work, client relations, and team relations.
Actively build upon client relationship efforts to market and cross‑sell the various services provided by the firm.
Acquire the skills necessary to develop quality client relationships and loyalty.
Support training and mentoring for staff and interns as necessary.
Perform other duties as assigned by the firm’s leadership.
Minimum Qualifications
Bachelor’s Degree in a quantitative field (or equivalent work experience), such as Statistics, Mathematics, Engineering, Computer Science, or similar.
Data affinity with attention to detail.
Solution‑ and problem‑solving orientation with an emphasis on product development, finding efficiencies, and streamlining processes.
Strong presentation and technical writing skills.
Able to quickly interpret data and transition it into tangible business recommendations, solutions, or analysis.
Experience using statistical computer languages (R, Python, SQL) to query databases, manipulate data, and draw insights from large datasets.
Occasional travel required (~20%).
Preferred Qualifications
Master’s Degree in Data Science, Data Analytics, or related field.
Advanced expertise with Python, Alteryx, and/or Tableau.
Experience using a broad range of quantitative analytical techniques, from descriptive statistical analysis to predictive and prescriptive analytics (e.g., linear and logistic regression, time series forecasting, clustering, classification, optimization, and model training and development). Demonstrated aptitude to determine the appropriate tool for each task.
Seniority level Not Applicable
Employment type Full‑time
Job function Research, Analyst, and Information Technology
Industry Professional Services
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Overview The Analytics team transforms data into actionable insights that fuel business growth. Using advanced tools in predictive analytics, machine learning, and AI, they help organizations unlock new opportunities, reduce risk, and improve efficiency. Their proprietary cloud‑based platform delivers timely, digestible insights that enhance strategy and performance. With a strong focus on data strategy, governance, and security, they ensure data quality and compliance—empowering clients to make confident, data‑driven decisions.
Responsibilities
Engage with clients professionally and consistently to understand their needs, deliver effective solutions, and build trust.
Support client engagements throughout all phases of the project lifecycle, including implementation and support of the tools and products we build.
Support tax, audit, and other teams with insights gained from analyzing data, automating tasks, and problem‑solving.
Utilize analytical, statistical, and programming skills to collect, analyze, and interpret data sets and develop data‑driven solutions to difficult business challenges.
Create client deliverables and technical documentation that clearly details analytic procedures, outputs and insights, and key reference information.
Perform core data analytic tasks, including designing and implementing procedures to collect, transform, cleanse, normalize, and analyze data; automating reports, dashboards, and other performance tools; providing ad‑hoc analysis and presenting results in a clear manner.
Maintain and achieve high quality in work, client relations, and team relations.
Actively build upon client relationship efforts to market and cross‑sell the various services provided by the firm.
Acquire the skills necessary to develop quality client relationships and loyalty.
Support training and mentoring for staff and interns as necessary.
Perform other duties as assigned by the firm’s leadership.
Minimum Qualifications
Bachelor’s Degree in a quantitative field (or equivalent work experience), such as Statistics, Mathematics, Engineering, Computer Science, or similar.
Data affinity with attention to detail.
Solution‑ and problem‑solving orientation with an emphasis on product development, finding efficiencies, and streamlining processes.
Strong presentation and technical writing skills.
Able to quickly interpret data and transition it into tangible business recommendations, solutions, or analysis.
Experience using statistical computer languages (R, Python, SQL) to query databases, manipulate data, and draw insights from large datasets.
Occasional travel required (~20%).
Preferred Qualifications
Master’s Degree in Data Science, Data Analytics, or related field.
Advanced expertise with Python, Alteryx, and/or Tableau.
Experience using a broad range of quantitative analytical techniques, from descriptive statistical analysis to predictive and prescriptive analytics (e.g., linear and logistic regression, time series forecasting, clustering, classification, optimization, and model training and development). Demonstrated aptitude to determine the appropriate tool for each task.
Seniority level Not Applicable
Employment type Full‑time
Job function Research, Analyst, and Information Technology
Industry Professional Services
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