Data Analyst
1 week ago
Job Title: Data Scientist
Department: Data & Analytics / Operations
Location: Onsite / Hybrid / Remote
Employment Type: Full-Time
Reports To: Director of Analytics / Head of Business Intelligence
The Data Scientist will play a key role in transforming operational data into actionable insights that drive performance, efficiency, and strategic decision-making across our BPO programs. This role will partner closely with Operations, Quality, Workforce, Training, and Client Stakeholders to analyze trends, optimize processes, improve customer experience, and support business growth through intelligent data modeling and analytics solutions.
Key Responsibilities- Collect, clean, and analyze large datasets from multiple sources (CRM, WFM, QA, Telephony/CCaaS, CSAT/NPS platforms, etc.)
- Build predictive and statistical models to forecast performance, identify patterns, and optimize operational workflows (e.g., staffing levels, handle time, conversion rates, quality scores).
- Develop dashboards and visualizations (Power BI, Tableau, or equivalent) to communicate insights to internal leadership and client stakeholders.
- Conduct deep-dive analyses to understand drivers of performance issues such as escalations, repeat contacts, customer sentiment trends, or sales conversion variances.
- Support automation and process improvement initiatives through scripting, data pipelines, and analytical tools.
- Collaborate closely with Workforce Management to support capacity planning and forecasting.
- Prepare data-driven recommendations for business reviews, client QBRs, and performance strategy meetings.
- Ensure data accuracy, integrity, and compliance with internal governance standards.
- Continuously explore new methodologies, tools, and best practices to enhance analytical maturity across the organization.
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or related field (Master's is a plus).
- 2+ years of experience in data analytics, business intelligence, or data science (BPO/Contact Center experience strongly preferred).
- Strong proficiency in SQL, Python or R.
- Experience working with BI visualization tools such as Power BI, Tableau, Qlik, or Looker.
- Strong knowledge of statistical modeling, predictive analytics, time series forecasting, and hypothesis testing.
- Familiarity with A/B testing, regression models, clustering, and classification algorithms.
- Ability to communicate complex data insights in a clear and compelling manner to non-technical stakeholders.
- Strong problem-solving skills and ability to handle multiple priorities in a fast-paced environment.
- Experience working with CCaaS platforms (e.g., Five9, Genesys, Talkdesk, Zendesk, NICE).
- Understanding of call center metrics such as AHT, CSAT, NPS, FCR, SLA staffing models, and service level optimization.
- Experience with ML model deployment and automation pipelines is a plus.
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