Workforce Planning / Data Analyst

Role Overview: Join our team and take a leading role in shaping workforce planning strategy through advanced forecasting, capacity planning, and optimization modeling. You will design scalable models to address complex contact center staffing challengesincluding inbound and blended multi-channel environmentswhere operational costs and efficiency must be continuously balanced to meet business goals. This role demands strong operations research expertise and proficiency in Python to automate data pipelines and integrate third-party optimization libraries, enabling intelligent and efficient workforce solutions.

Key Responsibilities: - Develop and implement long-term forecasting models to guide workforce planning, hiring plans, and budget allocation, incorporating skill-based constraints and relevant operational constraints. - Own your projects by managing daily activities and timelines, while collaborating with leadership to align staffing models with business objectives, seasonal demands, and evolving initiatives. - Proactively and creatively explore and propose strategies to enhance operational efficiencyfor example, by analyzing alternative scenarios with varying risk levels and weighing the trade-offs between hiring additional staff and leveraging overtime. - Translate operational requirements into mathematical optimization models to address workforce challenges, including multi-skill staffing and other operational constraints. - Conduct ad-hoc analyses to inform strategic decisions, leveraging tools like Python, R, or SQL, and integrate optimization solvers such as Gurobi, CPLEX, or open-source alternatives. - Act as a thought leader on research initiatives to advance workforce planning methodologies, including: - Develop Python-based automation to streamline forecasting and optimization processes, including automated data extraction, transformation, and model execution. - Optimizing blended inbound/outbound contact center staffing to balance cost and service levels.

Qualifications Required: - 3+ years of experience in data science, operations research, or related quantitative role or graduate coursework in supply chain management, statistics, industrial engineering, or management science. - Deep understanding of statistical modeling and optimization techniques relevant to contact center strategic planning and resource allocation. - Collaborate with cross-functional teams to identify and implement data-driven solutions. - Results-driven project leader with a proven track record of managing end-to-end project lifecycles. - Effectively communicate complex concepts and present insights to both technical and non-technical audiences with clarity and impact. - Demonstrates a problem-solving mindset with a focus on scalable solutions, strong attention to detail, and the ability to thrive in ambiguous situations. - Expertise in at least one scripting language (e.g., Python, R) and a strong knowledge of SQL and Excel. - Working knowledge of workforce management tools (e.g., Genesys, NICE, Aspect).

Additional Details: Omit this section as there are no additional details of the company included in the job description. Role Overview: Join our team and take a leading role in shaping workforce planning strategy through advanced forecasting, capacity planning, and optimization modeling. You will design scalable models to address complex contact center staffing challengesincluding inbound and blended multi-channel environmentswhere operational costs and efficiency must be continuously balanced to meet business goals. This role demands strong operations research expertise and proficiency in Python to automate data pipelines and integrate third-party optimization libraries, enabling intelligent and efficient workforce solutions.

Key Responsibilities: - Develop and implement long-term forecasting models to guide workforce planning, hiring plans, and budget allocation, incorporating skill-based constraints and relevant operational constraints. - Own your projects by managing daily activities and timelines, while collaborating with leadership to align staffing models with business objectives, seasonal demands, and evolving initiatives. - Proactively and creatively explore and propose strategies to enhance operational efficiencyfor example, by analyzing alternative scenarios with varying risk levels and weighing the trade-offs between hiring additional staff and leveraging overtime. - Translate operational requirements into mathematical optimization models to address workforce challenges, including multi-skill staffing and other operational constraints. - Conduct ad-hoc analyses to inform strategic decisions, leveraging tools like Python, R, or SQL, and integrate optimization solvers such as Gurobi, CPLEX, or open-source alternatives. - Act as a thought leader on research initiatives to advance workforce planning methodologies, including: - Develop Python-based automation to streamline forecasting and optimizat