Senior Level Data Analytics Intern Jobs
Senior level data analytics intern jobs place experienced analysts in ownership roles, leading project direction, shaping methodology, and guiding junior team members through complex data challenges. Openings concentrate across Technology & Software, Consulting & Professional Services, and Banking & Financial Services, with a strong mix of on-site, remote, and hybrid settings, and employers like Apple, JPMorganChase, and Ryder System hiring at this level now.
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Who We Are
DoubleVerify is a leading software platform for digital media measurement, data, and analytics. DV's mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world's largest brands, publishers, and digital ad platforms. DV's technology platform provides advertisers with consistent and unbiased data and analytics that can be used to optimize the quality and return on their digital ad investments. Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at doubleverify.com.
DV is looking for a strategic Client Analytics Lead with proven experience finding and telling stories in data to join our North America Client Analytics team. In this role you will work closely with Marketing, Product, Sales, and Sales Engineering teams to support a blue-chip client roster based primarily in the East Coast. DV is uniquely positioned in the industry, offering unparalleled exposure to top-tier clients across verticals, industry-wide trends, and a fast-paced, product-focused environment.
- Own the full lifecycle of client analytics deliverables, including QBRs, Test Wraps, and Custom Insights for a portfolio of DV's most strategic and high-revenue Global and East Coast accounts
- Serve as a primary analytics voice in client-facing presentations, translating complex DV data into actionable, strategic insights that drive client value
- Project manage and prioritize deliverables with limited supervision, proactively setting timelines and managing stakeholder expectations
- Proactively create, roll out, and refine processes and analytical best practices to be followed by the broader team
- Act as an advisor and resource to Client Insights Analysts on data methodology, DV product expertise, and data storytelling
- Lead strategic and ad-hoc discussions with clients and internal stakeholders, including commercial leadership up to the VP level
- Proactively identify and action on revenue opportunities emerging from client analytics work with Client Partners
- Contribute to knowledge sharing within the Client Analytics function, surfacing case studies, trends, and best practices that strengthen the broader team and DV
- Build strong feedback loops with Commercial partners (Client Partners, Group Directors, RVPs) to align analytics support with revenue priorities and escalate trends to leadership
Who You Are
- 6+ years of experience in an analytical capacity (research, data & analytics, or insights strongly preferred)
- Exceptional command of Excel and PowerPoint, including advanced functions, pivot tables, and data visualization
- Exceptional understanding of DV products, databases, and their applications to clients; familiarity with Salesforce, Looker, Snowflake, and/or SQL
- Strong data storytelling skills, you can take a complex dataset and turn it into a clear, compelling narrative for both technical and non-technical audiences
- Proven ability to project manage client deliverables independently, meeting SLAs and proactively communicating timelines and risks
- Experience leading client-facing presentations and strategic discussions with senior stakeholders
- Solution-oriented: you work on issues of diverse scope, evaluate a variety of factors including business context and trends, and are proactive in finding and presenting solutions
- Proactive contributor to team culture: you share insights, flag trends, learnings, etc.
- Digital media, ad tech, or agency experience strongly preferred
- Client-facing experience required (presenting, reporting, and relationship management)
- Ability to travel as needed for client engagements
- Comfortable leaning into AI tools and eager to help shape how the team uses them to work smarter, move faster, and unlock more creative approaches to analytics and client storytelling
The successful candidate's starting salary will be determined based on a number of non-discriminating factors, including qualifications for the role, level, skills, experience, location, and balancing internal equity relative to peers at DV. The estimated salary range for this role based on the qualifications set forth in the job description is between $100,000 to $163,000. This role will also be eligible for bonus/commission (as applicable), equity, and benefits. The range above is for the expectations as laid out in the job description; however, we are often open to a wide variety of profiles, and recognize that the person we hire may be more or less experienced than this job description as posted.
Not-so-fun fact: Research shows that while men apply to jobs when they meet an average of 60% of job criteria, women and other marginalized groups tend to only apply when they check every box. So if you think you have what it takes but you're not sure that you check every box, apply anyway!
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Find JobsSenior Level Data Analytics Intern Job Market
Who's Hiring
- Apple32

- JPMorganChase24

- Ryder System22

- CVS Health21

- Citi15

Top Industries Hiring
- Technology & Software186
- Consulting & Professional Services100
- Banking & Financial Services82
- Biotechnology & Pharmaceuticals79
- Healthcare & Medical Services72
Senior Level Data Analytics Intern Jobs: Frequently Asked Questions
How do I get a senior level data analytics intern job?
Employers at this level want candidates who have led analytics projects end to end, not just contributed to them. Demonstrating ownership of a model, pipeline, or reporting framework matters more than breadth alone. Strong candidates can speak to decisions their analysis drove, have experience mentoring peers, and bring fluency in tools like SQL, Python, or Tableau alongside a clear point of view on data strategy.
Which companies hire senior level data analytics interns?
Companies hiring senior level data analytics interns right now include Apple, JPMorganChase, and Ryder System, based on current listings on Migrate Mate as of July 2026. Hiring at this level tends to come from organizations large enough to have dedicated analytics functions, including technology firms, financial services companies, and consulting practices with data-intensive client work.
Are there remote senior level data analytics intern jobs?
Yes, remote availability is real at this level, though it varies by employer and function. About 39% of senior level data analytics intern openings are remote or hybrid as of July 2026, reflecting how many organizations treat experienced analytics professionals as capable of working independently across distributed teams. On-site roles exist primarily where data governance or collaboration requirements are stricter.
What makes a data analytics intern role senior level?
Senior level data analytics intern roles are defined by scope and ownership rather than task execution. Expectations include designing analytical frameworks, owning deliverables from question to recommendation, and often guiding less experienced analysts through methodology or tooling decisions. The work involves more ambiguity, higher-stakes outputs, and cross-functional accountability than mid-level roles, which tend to operate within more defined parameters and under closer direction.
Which industries hire the most senior level data analytics interns?
Senior Level data analytics intern roles concentrate in Technology & Software, Consulting & Professional Services, and Banking & Financial Services, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they generate large, complex datasets that require experienced analysts who can translate findings into decisions, not just reports.