About Data & Analytics
Data & Analytics Team unifies data and analytics talent responsibly leverage data to build competitive advantages for our businesses with value and protection for customers. The team encompasses a variety of data and analytics disciplines, from data governance and data strategy/partnerships to reporting, data science and machine learning, and are actively engaged in ensuring impact at the front-line and for our customers through Sales, Marketing and Operations transformations. We have a strong partnership with our dedicated Technology partners, who provide us with our cutting-edge data and analytics infrastructure. Joining Data & Analytics means you sit in the engine that powers with insights, providing an opportunity to materially impact both our customer and business outcomes. The team also offers significant learning and mobility opportunities for career development and future growth.
Position Overview
Drive production-grade delivery of Quality as a Service (QaaS) analytics to support firmwide QA/QC automation with LLM-powered insights. Senior consultants will build and optimize Tableau dashboards, engineer Snowflake ETL, automate reporting pipelines in Python/SQL/Alteryx/Snowflake, and optionally develop Python modules to operationalize transcript-based insights. This is a hands-on builder role with clear SLAs, documentation, and handover requirements. Role backgrounds may include Senior Data Engineer, Senior Data Scientist, or Senior Data Analyst.
Core Responsibilities
- Data validation and quality assurance across pipelines, enforcing schema conformity, lineage, and DQ rules.
- Deep-dive analysis integrating multiple data sources (e.g., voice, web, CRM), with reconciliation and triangulation to resolve discrepancies.
- Statistical analysis: sample size, A/B Testing and power determination, confidence intervals, and model accuracy/precision assessment (calibration, lift).
- Data mining using Python and SQL across structured (tables) and unstructured data (transcripts, logs), including feature engineering and pattern detection.
- Connecting agents to call metrics outcome and deep dive analysis highlighting opportunities for agent coaching.
- Work with the product and technology to provide insights and support for LOB expansion and insights.
- Partner with cross function team for building report and provide analytics mapping to insights.
Tableau (primary)
- Design and publish executive-ready dashboards; implement filters (Product, Queue, LOB), DoD/MoM change, KPI cards, drill downs, and performance tuning.
- Manage Tableau Server artifacts (projects, permissions, extracts, schedules).
Snowflake ETL (primary)
- Develop SQL models (tables/views), ingest structured and semi-structured JSON, and implement DQ checks (duplicates, nulls, type conformity).
- Orchestrate Snowflake tasks/streams for scheduled refresh; align with weekly → daily cadence.
Alteryx Automation (primary)
- Build parameterized workflows for ingestion, transformations, and quality rules; schedule and monitor runs; log and remediate pipeline failures.
Python (LLM insights)
- Create lightweight modules to derive transcript-based insights (e.g., intents, outcomes, invalid transfers) and sentiment features; package for pipeline integration.
Quality as a Service integration
- Operationalize call quality scoring inputs (AHT, transfers, repeat calls, invalid transfers) and MLIO call reasons; ensure consistent taxonomy (L1–L3).
Governance, SLAs, and documentation
- Adhere to DUC/access controls; maintain data dictionaries, runbooks, and change logs.
- Meet agreed refresh SLAs (weekly; migrate to daily when feeds are available); ensure auditability and lineage.
Required Qualifications
- 5+ years delivering enterprise analytics solutions.
- Tableau (Desktop/Server): advanced calc fields, LODs, table calcs, extract scheduling, performance optimization.
- Snowflake SQL: complex joins, window functions, semi-structured data (VARIANT/JSON), tasks/streams.
- Alteryx Designer: ETL/automation, error handling, scheduling, and workflow governance.
- Strong SQL/Python fundamentals; Git-based versioning; clear documentation and stakeholder communication.
- Proven experience in operations/contact center or servicing analytics (AHT, transfers, repeat calls, QA metrics).
- Executive-ready communication: concise narratives, clear options/recommendations, and stakeholder alignment.
- A/B and pre/post measurement design; KPI definition and benefits quantification (FTE/time to feedback).
Desired Qualifications
- NLP/LLM experience (prompt design, text feature engineering, lightweight inference pipelines).
- Data quality and controls: rule frameworks, monitoring, alerting, and incident remediation.
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