Senior Team Lead, Content Analysis
Govini
People & HR
Pittsburgh, PA, USA
Company Description
Job Description
We are seeking an exceptional and experienced Senior Team Lead for the Content Analysis team, a role for someone who shares our passion and obsession with quality. You will be a core member of our Product and Engineering team dedicated to helping our clients replace time-consuming, manual processes to achieve informed, real-time decisions about government markets, competitors, and agency relationships. The ideal candidate is a hands-on analyst with large dataset experience. You must also possess strong interpersonal skills to work cross-functionally across internal teams and with Govini platform Subject Matter Experts (SMEs).
You will support the Content Analyst Manager in overseeing two offshore teams across split shifts, ensuring the delivery of high-quality, fast-turn validation and QA. This role involves assisting with day-to-day team management, workload prioritization, and performance support while maintaining high-confidence accuracy across every data point. You will own feedback loops and process improvements—leveraging technical skills to reduce rework, improve scalability, and strengthen overall execution—while reporting progress, risks, and outcomes directly to the Content Analyst Manager.
This role is a full-time position located out of our office in Pittsburgh, PA.
This role may require up to 10% travel
Scope of Responsibilities
The Senior Team Lead manages and provides leadership for two offshore teams, overseeing daily workflow, assignments, prioritization, throughput, and SLA delivery. This includes consistent coaching (calibrations, feedback, 1:1s/lead check-ins) to maintain morale and accountability across different cultures and hours, as well as escalating risks, resourcing gaps, and performance concerns to the Content Analyst Manager.
The role also involves overseeing manual QA and validation, especially for high-volume checks with quick turnaround. Key responsibilities include triaging requests, prioritizing workloads, meeting SLAs, establishing feedback loops to reduce errors and improve accuracy, and documenting issues and resolutions to enhance future execution. Daily/weekly status updates on volume, trends, and blockers are required.
Further responsibilities encompass maintaining and improving SOPs, QA guidelines, and validation standards; tracking key performance metrics and risks; leading calibration and review routines; and supporting performance coaching and skill development.
Qualifications
- U.S. Citizenship is required
- 3+ years of experience in content operations, data operations, research operations, data QA/validation, or similar roles supporting structured data workflows
- 1–3+ years experience leading analysts or data QA teams (including offshore and/or shift-based coverage preferred)
- Proven ability to manage high-volume validation work with tight SLAs, competing priorities, and frequent context switching
- SQL and Python experience
- Experience working with structured datasets, logs, and validation outputs to identify root causes and reduce rework
- Familiarity with data QA concepts (sampling methods, error categorization, trend tracking, and continuous improvement loops).
- Demonstrated success in coaching teams, improving performance, and maintaining high-quality standards
- Strong judgment and attention to detail when validating complex relationships and resolving ambiguous cases
- Excellent written communication — able to document decisions with clear reasoning and auditable source support
- Ability to prioritize, triage, and execute quickly while maintaining consistent quality
- Strong stakeholder communication skills and the ability to coordinate across multiple workstreams
- Comfortable operating in a “supporting leader” capacity and reporting outcomes, blockers, and risks upward
- Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Ability to translate operational problems into simple technical solutions (query-based checks, automated sampling, error flagging, process instrumentation)