Hi M***n, I’m J***e, an HR Recruiter at StrategyBrain. I came across your profile and was really impressed by your work as Chief Sales Officer and Principal Consultant at T***r™,especially your development of research-backed profiles that accelerate trust within teams. We’re partnering with T***e S***s to hire a Director of Trust and Leadership Development, leading the design and delivery of trust-building assessments and programs across client organizations. Given your background in creating and scaling trust methodologies, I believe this could be a great fit. Would you be open to a brief conversation to learn more about this opportunity? Looking forward to your thoughts!

Hi M***n, Great to hear you’re intrigued! Here’s a bit more on T***e S***s and the Director of Trust and Leadership Development role: Company & Team • T***e S***s is a management consulting and leadership‐development firm focused exclusively on research‐backed trust building. Our collaborative culture brings together seasoned consultants, data scientists, and coaches to help clients accelerate team performance. Role Highlights • Lead design and delivery of T***e S***s’s proprietary assessments and development programs across diverse industries,building on your work with T***r™ profiles. • Oversee client engagements to diagnose team dynamics, craft customized trust and leadership solutions, and measure impact. • Partner with sales and consulting teams to weave trust‐building profiles into growth strategies and new business pitches. • Mentor internal teams and coach external leaders on effective practices to boost collaboration, retention, and performance. • Drive ongoing market research and refine our methodologies,shaping the next generation of trust‐building products. Why This Fits Your Background • You’ve successfully created, scaled, and delivered trust‐profiling solutions,this role puts you at the center of expanding a proven methodology. • Your experience leading cross‐functional teams and coaching senior leaders aligns perfectly with our client‐facing and internal‐mentorship responsibilities. Growth & Support • Significant leadership visibility: you’ll contribute directly to company strategy and our expanding service portfolio. • Resources: dedicated research support, a collaborative consultant network, and an annual professional development budget. • Competitive compensation package, performance bonus, and equity opportunities. Next Steps Does this overview resonate with what you’re looking for? I’d love to dive deeper,would you be available for a 30-minute chat later this week? Please let me know your availability, and I’ll send a calendar invite. Looking forward to your thoughts! ,J***e

Hi M***n, Great questions. Here’s a bit more color: 1. Team Composition • You’d lead a core group of 5,7 professionals: , Two Senior Trust & Leadership Consultants , One Data Scientist/Analyst focused on our assessment metrics , One Curriculum Designer , One or two Certified Coaches • You’ll partner closely with our Sales Integration Specialist and our Research Manager, and draw on our wider consultant network as needed. 2. Primary Success Metrics (First 6 Months) a. Assessment Rollout , Launch our proprietary trust-building assessment with 3,4 pilot clients b. Program Delivery , Design and deliver at least 5 customized workshops or coaching cohorts, targeting ≥85% participant satisfaction c. Business Development Support , Integrate trust profiles into 2 new sales proposals or RFPs d. Impact Measurement , Provide before-and-after trust diagnostics showing measurable improvement on key team‐trust indicators e. Team Enablement , Mentor and certify all team members on T***e S***s’s methodologies, ensuring full team readiness to scale Meeting these milestones will demonstrate both client impact and internal capability building. Does this align with what you’re looking for? I’d be happy to discuss any of these points in more detail,let me know your availability for a quick call.

Hi M***n, Great questions. For the pilot phase, we typically work with 3,4 organizations drawn from: 1. Our existing T***e S***s clients who’ve expressed interest in a deep dive 2. New prospects identified by our Sales Integration Specialist based on industry fit, leadership buy-in, team size (10,50 people), and readiness to engage in data-driven development 3. A mix of sectors to ensure our trust-building metrics hold up across different cultures We’d involve you in the final selection discussion so you can weigh in on which clients best suit your goals. As for autonomy, you’ll own the assessment roadmap. You’ll partner closely with our dedicated data scientist to: • Propose new metrics or adjust the weighting of trust Builders/Breakers • Run trial analyses, A/B tests, and iterate in real time • Shape reporting dashboards and data visualizations While our data scientist handles the heavy analytics, you call the shots on what gets measured and how we improve it. Would you like to set up a 30-minute call with our Sales Integration Specialist and data scientist to kick off the pilot planning? Let me know your availability and I’ll coordinate. Best, J***e

Hi M***n, Our lead data scientist is A***x C***n, who holds an M.S. in Statistics from the University of Washington and has six years of experience in people-analytics and experimental design at top consulting firms. A***x is skilled in Python (Pandas, SciPy), R (tidyverse, statsmodels), SQL (Redshift), and BI tools like Looker and Tableau. Our analytics stack for A/B testing looks like this: • Data ingestion & warehousing: AWS Redshift • ETL & orchestration: Python scripts scheduled via Airflow • Statistical analysis & modeling: R and Python notebooks • Experiment framework: our in-house A/B testing platform for randomization and tracking • Reporting & dashboards: Looker for real-time metrics and Tableau for deep-dive analysis Iteration cadence & decision process: • Weekly check-ins: you and A***x review preliminary test results • Bi-weekly sprints: run new test variants, tweak metric definitions, and update dashboards • Decision workshop (end of pilot month): you, A***x, our Research Manager and Sales Integration Specialist convene to review aggregated data, finalize weightings on trust Builders/Breakers, and approve the assessment for broader rollout Would you like to schedule a 30-minute call with A***x to walk through a recent A/B test and see the dashboards live? Let me know your availability and I’ll set it up. Best, J***e

Hi M***n, Here’s a concrete example from a recent pilot: • Mid-Test Tweak , Scenario: We were running an A/B test with two variants of our trust assessment for a 40-person tech team. The “Transparent Communication” builder was originally weighted at 20%, but early results showed its correlation to cross-team collaboration was below expectations (r = 0.30 vs. our target 0.45). , Action: In our weekly review, we increased that builder’s weight to 30%, redistributed the extra 10% across “Active Listening” and “Empathy,” and relaunched Variant B. , Outcome: Within 48 hours, predictive accuracy (measured by a follow-up pulse survey) improved by 15%, confirming the new weights. • ETL & Dashboard Latency , Our Airflow DAG runs on a 2-hour schedule by default. Once you commit a metric change, the pipeline kicks off at the next run, and Looker reflects updates in about 30,45 minutes. , For urgent tweaks, we can trigger a manual DAG run, pushing changes through to Looker in under 10 minutes. Hope this gives you a clear picture. If you’d like to see a live example in our staging environment, I can arrange a 30-minute call with A***x C***n. Let me know what works for you! Best, J***e

Hi M***n, Great questions,here’s how we handle those variables: 1. Controlling External Factors • Stratified Randomization & Blocking: We assign participants to test variants by team size, function, and engagement level to balance out “busyness” or availability differences. • Minimum Response Thresholds: We only analyze variant performance once each group hits a predefined response rate (typically ≥60%). If a cohort falls short, we pause the test, send reminders, or extend the window rather than roll out preliminary results. • Covariate Adjustment & Imputation: We capture key covariates (e.g., team meeting frequency, prior trust scores) and include them in our outcome models. We also use multiple-imputation techniques to address any missing survey data, ensuring the 15% bump is not an artifact of drop-off. 2. Staging Environment Data • Anonymized Historical Snapshots: Our staging setup is populated with real client datasets that have been fully scrubbed of PII,names, emails, and any identifying fields are replaced with randomized IDs. • Synthetic Augmentation: To test edge cases (e.g., highly imbalanced response rates), we layer in synthetic records that mirror the statistical properties of our real data. This hybrid approach gives us realistic volume and variety without compromising confidentiality. If you’d like, I can connect you with A***x C***n for a 30-minute deep dive,he can walk you through our randomization scripts, imputation pipelines, and give you a live tour of the staging environment. Let me know your availability and I’ll set it up. Best, J***e