Senior Data Analyst at Codeandtheory

Code and Theory is hiring Data Analysts within our Intelligence team — providing the quantitative backbone for engagements that range from pipeline strategy and account development to data ecosystem audits and partner program design. You'll be deployed across the firm's strategic engagements, embedding with teams and client partnerships to produce the analysis that shapes decisions. This is not a reporting role. You'll be the person in the data producing the evidence that shapes strategic decisions: pulling CRM exports and finding the patterns that tell us directions to pursue, auditing data ecosystems and mapping where information breaks down across systems, building the analysis that turns a hypothesis into a case for action. Some deployments are commercially focused: account research, pipeline analysis, market sizing, competitive intelligence, and the quantitative inputs that power go-to-market strategy. Others are infrastructure-focused: auditing how data flows across CRM, partner portals, and marketing platforms, assessing data quality, mapping integration gaps, and building the analytical foundation for operating model design. We're hiring multiple people into this role. Each will have a primary deployment, but the analytical skills are transferable across engagement types — the person who can map pipeline conversion patterns can also map data ecosystem gaps. What's consistent is that you're working with real data to produce real findings that directly inform what the team does next. WHAT YOU'LL DO • Conduct deep-dive quantitative research on target accounts: financial performance, technology investments, market positioning, growth signals, and competitive dynamics • Analyze pipeline data to identify conversion patterns, stall points, and whitespace across account portfolios • Produce the quantitative inputs for account prioritization: deal size estimates, market sizing, competitive threat assessment, propensity-to-engage scoring • Build and maintain structured account research databases — clean, current, and accessible to strategists and engagement teams • Support business consultants with the data behind their recommendations: when they build the case for why a prospect should engage, you produce the evidence • Data ecosystem auditing and mapping • Audit data sources across client environments: CRM systems, partner portals, marketing platforms, deal registration systems, account mapping tools, and field intelligence • Map how data actually flows — where it's captured, who owns it, how reliable it is, where it breaks down, and where silos prevent connected decision-making • Assess data quality: completeness, accuracy, consistency, timeliness, and fitness for the analytical and operational purposes it needs to serve • Produce data ecosystem maps and gap analyses that become the foundation for architecture and operating model recommendations • Trace attribution and measurement paths: how pipeline, revenue, and partner influence are tracked today vs. how they need to be tracked • Analysis and intelligence • Build financial models, market sizing analyses, competitive benchmarks, and scenario analyses that inform strategic recommendations • Produce the quantitative sections of client deliverables: findings decks, assessment reports, business cases, and program reviews • Design and build reporting frameworks: define what to measure, how to collect it, and how to present it so decision-makers can act on it • Support measurement strategy development: help define KPIs, establish baselines, and build the tracking methodology for ongoing programs • Conduct primary data collection when needed: surveys, structured interviews, and field data gathering • Dashboard and reporting development • Build and maintain dashboards and reporting tools that make data accessible and actionable — pipeline trackers, program health scorecards, competitive positioning monitors, and performance dashboards • Integrate data from multiple sources into unified views: CRM, social listening, media monitoring, partner platforms, and internal tracking systems • Iterate on reporting based on stakeholder feedback — the first version is never the last version WHAT YOU'LL NEED • 5-7 years in data analysis, business intelligence, or analytics roles — ideally within management consulting, enterprise technology, SaaS, or professional services environments • Demonstrated experience working with CRM data (Salesforce strongly preferred), marketing platforms, and/or partner ecosystem tools (Crossbeam, partner portals, deal registration systems) • Track record of producing analysis that directly informed strategic or commercial decisions — not just reporting on what happened, but shaping what happened next • Experience with data auditing, data quality assessment, or data ecosystem mapping is a strong differentiator • Background in management consulting analytics teams (BCG, McKinsey, Bain, Deloitte, Accenture) or in-house analytics at enterprise technology companies is highly valued • Treats data as a means to a decision, not an end in itself — you're always working toward "so what does this mean and what should we do about it" • Comfortable in ambiguity — some engagements have clean data sets and clear questions; many don't, and you'll need to figure out where the data is, whether it's trustworthy, and what it can tell you • Curious about the business context, not just the numbers — you want to understand why the pipeline stalls at a certain stage, not just that it does • Detail-oriented without losing the thread — you catch the data quality issue that would invalidate the analysis, but you also know when to zoom out and deliver the finding • Proactive — you surface insights the team didn't ask for because you saw something in the data worth flagging • Advanced proficiency in Excel/Google Sheets and SQL • Experience with data visualization and dashboarding tools (Tableau, Looker, Power BI, or equivalent) • Proficiency in Salesforce reporting and data extraction; experience with Salesforce data architecture is a plus • Comfort with statistical analysis and basic modeling: regression, segmentation, cohort analysis, forecasting • Experience integrating and reconciling data from multiple platforms and sources • Clear communication skills — you can present a complex finding to a non-technical audience in a way that drives action, not confusion • Familiarity with the enterprise SaaS landscape, particularly the Adobe ecosystem and partner program infrastructure, is a strong differentiator ABOUT US Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic. Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok. The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team. The base compensation range for this role is $80,000 – $110,000 and spans multiple levels. We're open to hiring at the level that best matches the right candidate's experience. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, budget, and location.