AI Strategist, Data — Applied Analysis, Visibility Intelligence & Client Insight

Upcoming Role · Remote (USA or Europe)

The way people discover information online is changing. AI systems are increasingly shaping which brands are surfaced, how companies are described, and what information gets prioritized across search and answer experiences. Ansvisor helps organizations understand that visibility and act on it with more precision.

As this landscape evolves, the ability to interpret prompt-level behavior, visibility patterns, and AI-generated output is becoming increasingly valuable. We anticipate opening an AI Strategist, Data role to help turn raw data into structured insight and strategic recommendations for customers operating in this new environment.

This role will sit close to the intersection of analytics, client strategy, and applied AI research. We’ll be looking for someone who is comfortable working directly with messy or large-scale datasets, curious about how LLM-driven systems behave, and able to translate technical analysis into clear commercial and strategic implications.

This is a hands-on role for someone who likes real data, ambiguous questions, and practical outputs.

About the Role

This role will focus on analyzing how brands appear across AI-driven discovery environments and helping turn those findings into useful guidance for customers and internal teams.

You will likely work across:

• Prompt and response-level analysis
• Brand visibility and mention patterns
• LLM behavior and answer variation
• Query clustering and classification
• Structured and unstructured data interpretation
• Client-facing insight development
• Internal collaboration across product, customer-facing teams, and leadership

The work will likely involve both technical execution and strategic synthesis. You’ll be expected not only to run analysis, but also to help explain what the findings mean and where action should follow.

What We’ll Likely Look For

We’re interested in people who can move comfortably between data, questions, and interpretation.

You may be a strong fit if you:

• Are comfortable writing SQL and working directly with underlying datasets
• Can analyze large volumes of structured and semi-structured data with care and precision
• Are curious about how AI systems behave and where patterns emerge across prompts, outputs, and visibility outcomes
• Can use AI-assisted workflows to classify, organize, and synthesize large amounts of information
• Are able to turn analysis into clear recommendations rather than just reporting observations
• Communicate well with both technical and non-technical stakeholders
• Like working at the edge of product, data, customer strategy, and market interpretation
• Bring ownership to ambiguous problems and know how to push analysis toward an answer

We’ll value someone who is analytical, practical, and strong at connecting technical findings to real decisions.

What You’d Be Expected to Do

While this role is not open yet, we expect responsibilities to include:

Data and Visibility Analysis

• Working with prompt-level, response-level, and account-level datasets to understand brand visibility patterns
• Writing SQL to extract, organize, and analyze large-scale data relevant to AI discovery behavior
• Identifying trends across prompts, entities, citations, references, and answer characteristics
• Exploring how visibility shifts across platforms, question types, or content patterns

Applied AI and Research Work

• Using LLM-based workflows to classify, cluster, summarize, and interpret unstructured data
• Investigating patterns in AI-generated outputs and how they affect brand representation
• Supporting deeper analysis into answer quality, presence, consistency, and coverage across environments
• Helping turn exploratory research into repeatable analytical methods where useful

Strategic Insight Development

• Translating analysis into concise outputs that can support customer strategy and internal decision-making
• Helping explain what findings mean in practical terms for visibility, performance, and prioritization
• Producing work that can be used in senior-level conversations with clarity and confidence
• Surfacing recommendations, not just findings

Cross-Functional Collaboration

• Working closely with customer-facing teams, product, research, and leadership
• Supporting strategic customer work where deeper analytical interpretation is needed
• Feeding insight back into product thinking, methodology, and broader category understanding
• Helping connect technical investigation with commercial relevance

You Might Be a Fit If…

You like working with real data

You’re comfortable going into raw datasets, asking follow-up questions, and investigating until the pattern actually makes sense.

You’re analytical but practical

You don’t stop at “interesting.” You want analysis to lead to a clearer decision, stronger recommendation, or better strategy.

You’re curious about AI behavior

You want to understand how LLM-driven systems surface brands, how outputs vary, and where structure can be found in what looks messy at first.

You communicate clearly

You can explain technical findings in a way that remains accurate but becomes useful to broader teams and customers.

You take ownership

You’re proactive, self-directed, and comfortable pushing work forward without waiting for every step to be defined.

Likely Requirements

We expect this role to be best suited to someone with:

• Experience in analytics, data, operations, research, technical consulting, or a related role
• Comfort writing SQL and working directly with structured datasets
• Experience analyzing data in a business, product, or customer-facing context
• Strong written and verbal communication skills
• Curiosity about AI systems, search behavior, and data-driven strategy
• Ability to work independently in a remote role across the USA or Europe

Strong Signals

These are not strict requirements, but they would stand out:

• Experience with dashboards or analytics tools such as Retool, Looker, Tableau, or similar
• Experience using AI tools or LLM-based workflows in practical analytical work
• Familiarity with prompt analysis, classification, clustering, or other unstructured data tasks
• Experience working across product, engineering, customer success, or strategic accounts
• Experience in SaaS, AI, analytics, search, or digital visibility-related environments
• A habit of investigating edge cases and asking stronger second-order questions

Why This Role Matters

Ansvisor operates in a category where insight depends on more than traditional analytics. Understanding how brands appear in AI-driven environments requires new forms of analysis, new methods of interpretation, and people who can connect that work to practical action.

The person in this role would help build that capability. Their work would influence customer strategy, internal product thinking, and the way Ansvisor interprets a fast-changing landscape. This is an opportunity to work directly on the data layer behind an emerging category.

Role Status

This is an upcoming role, not an actively open position today. We’re sharing it because we expect it to become an important hire as the company grows, and we’d like to hear from people who may be a strong fit when the time comes.

Location: Remote
Regions: USA or Europe

How to Express Interest

If this role sounds aligned with your background, feel free to send us:

• Your CV or LinkedIn profile
• A short note on why this role interests you
• Optional: examples of analytical work, SQL projects, dashboards, research, or AI-related workflows you’ve built or contributed to

Send details to: career@ansvisor.com

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