Okay, I've searched for remote Lead Data Scientist roles in the high tech industry based in the United States, requiring 7+ years of experience and a Bachelor’s degree or higher. I have found 132 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Lead Data Scientist role is fundamentally about driving operational excellence and strategic impact through data at scale within Meta’s Edge Network Services initiative. The core purpose is to lead the M360 Analytics project to improve efficiency, optimize financial tracking, and provide actionable insights that steer decision-making. Beyond technical expertise, this role requires translating complex data challenges into scalable solutions—designing robust pipelines, governing layered operational metrics (L1/L2/L3), and automating critical financial systems (Opex and Capex tracking). The leadership dimension means mentoring junior staff, ensuring data quality and governance, and collaborating closely with diverse teams like engineering, finance, and operations. Technical mastery in SQL, Python or R, visualization tools, big data technologies, and cloud platforms will be exercised daily. Success here means reliably delivering high-impact insights, creating self-service analytics that empower stakeholders, and fostering a data-driven culture. The job demands strong autonomy and strategic judgment to prioritize data initiatives, navigate ambiguity in a fast-paced, technologically sophisticated environment, and communicate clearly to senior leadership for informed decisions.

Company Analysis:

Insight Global operates as a global staffing and professional services firm, specializing in connecting top technical talent with Fortune 1000 companies, including high-tech giants like Meta. Their positioning as both a talent provider and technical solution partner creates a dynamic environment where roles like this blend deep technical capability with adaptability and people leadership. The company appears to value empowerment, professional growth, and delivering measurable business impact to clients. Insight Global’s extensive global footprint and expertise in diverse industries suggest a mature organization that thrives on collaboration between recruiters, technical consultants, and client teams. For a candidate, this means working in a fast-moving, client-focused context requiring resilience, strong communication, and stakeholder management skills. The role’s long-term remote contractor status also points toward autonomy and self-motivation as critical factors. Strategically, this role aligns with Insight Global’s mission to embed high-value technical talents within client projects that drive operational innovation—highlighting the importance of both technical leadership and cultural fit to ensure long-term success and mutual growth.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Can you describe a time when you led a data science project involving multiple departments? How did you manage stakeholder expectations and ensure alignment?
• Behavioral: Tell me about a situation where you mentored junior data scientists. What was your approach, and what were the outcomes?
• Behavioral: Describe a time when you encountered data quality or governance issues. How did you identify and resolve them?
• Behavioral: Share an experience when you had to present complex data insights to senior leadership. How did you tailor your communication?
• Technical/Role-Specific: How would you approach designing scalable data pipelines for a high-volume, operational dataset like those used in ENS?
• Technical/Role-Specific: Walk me through your process for defining and implementing layered operational metrics (L1/L2/L3) to monitor performance.
• Technical/Role-Specific: Which data visualization tools have you used to build self-service analytics platforms, and how do you ensure they meet diverse user needs?
• Technical/Role-Specific: Explain your experience with big data technologies like Spark or Hive, particularly in relation to ETL and data warehousing.
• Situational: Imagine the Opex tracking automation system you developed starts producing inconsistent financial reports. How would you troubleshoot and resolve this?
• Situational: You receive conflicting requests from engineering and finance teams regarding metric definitions. How do you reconcile these differences and move forward?
• Situational: If a junior data scientist on your team is struggling with a complex modeling task, how do you support them while ensuring project deadlines are met?
• Company Fit/Motivation: What attracts you to working with Insight Global and the opportunity they offer through this Meta-related project?
• Company Fit/Motivation: How do your professional values and leadership style align with Insight Global’s emphasis on empowering people and delivering client success?
• Company Fit/Motivation: Given this is a fully remote contract role, how do you ensure productivity, collaboration, and team cohesion in such an environment?
• Questions for Interviewer: How does Insight Global measure success for this Lead Data Scientist role within the M360 Analytics project over the first year?
• Questions for Interviewer: Can you describe the team structure and cross-functional partnerships I would engage with most frequently?
• Questions for Interviewer: What are the biggest challenges Insight Global anticipates in delivering the ENS analytics solutions, and how can this role contribute to overcoming them?