Senior Manager, Analytics Applied AI

Job Description:

Senior Manager Analytics - Applied AI

Merkle Analytics Applied AI Practice

Merkle is a leading data-driven technology-enabled global performance marketing agency that specializes in the delivery of unique personalized customer experiences across platforms and devices. Our Analytics Applied AI Practice is at the forefront of implementing cutting-edge artificial intelligence solutions with particular expertise in knowledge extraction and insights generation systems that transform how our clients engage with their structured and unstructured data. We also help clients deeply understand AI system performance through rigorous evaluation frameworks and continuous improvement cycles. The Senior Manager Analytics - Applied AI is a critical leadership role within our growing practice. This position sits at the intersection of technical credibility delivery leadership and client engagement for complex AI systems. You will be responsible for leading the delivery of production-grade AI solutions including conversational analytics agentic workflows and AI evaluation programs while positioning clients for long-term ownership of the systems we build together. We are looking for a technically credible leader who combines deep Analytics DNA with handson AI experience and the ability to lead small teams through client engagements. This role sits within our innovation arm so were looking for someone who is innovative and researchoriented and comfortable turning emerging approaches into practical client solutions. Youll work closely with clients and our technical team to translate business requirements into scalable reliable AI systems. This role requires someone equally comfortable whiteboarding architecture with engineers and communicating technical concepts to non-technical leaders. Responsibilities: Lead the delivery of knowledge extraction and insights generation systems including conversational analytics text-to-SQL solutions unstructured data processing and agentic workflows that unlock value from client data at scale Own client relationships as the technical lead for complex AI engagements translating business requirements into technical approaches and communicating progress risks and results to non-technical stakeholders Lead AI evaluation engagements that help clients understand how their AI systems are performing assessing accuracy reliability and business impact while building continuous improvement cycles Guide the design and implementation of semantic layers and data architectures that enable accurate natural language interfaces across complex enterprise data environments Lead small teams (2-5 practitioners) through the full delivery lifecycle: requirements gathering solution design implementation evaluation framework creation and successful client handoff. Ensure clients are positioned to own and evolve the systems we build. Establish and execute evaluation frameworks including golden datasets accuracy metrics quality benchmarks and business impact measurement both for systems we build and as standalone evaluation engagements for clients Drive technical quality through architecture reviews solution design guidance and hands-on contribution where needed while enabling your team to do the primary build work Champion system transparency and explainability ensuring clients deeply understand how AI systems make decisions and where limitations exist Contribute to the technical roadmap for AI Analytics capabilities including evaluation of emerging technologies proof of concepts for new approaches and methodology development Stay current with the evolving AI landscape synthesizing research whitepapers and industry best practices into practical frameworks and approaches that advance our capabilities and benefit our clients Represent the practice in client presentations internal knowledge sharing and thought leadership that positions Merkles Analytics Innovation team as a leader in applied AI Develop team members by providing technical mentorship delivery coaching and career guidance to AI practitioners on your engagements Experience: 7 years in analytics data science or related fields with at least 3 years focused on AI/ML systems preferably including knowledge extraction conversational analytics or insights generation implementations Track record leading small teams or workstreams through technical delivery whether as a tech lead engagement manager or senior practitioner who guided junior team members Demonstrated ability to communicate technical concepts to non-technical audiences. You can explain how an AI system generates insights to a marketing executive and why evaluation metrics matter to non-technical leaders. Deep familiarity with cloud data platforms. Stack agnostic but specific experience in Databricks (Unity Catalog Genie) or Snowflake (Cortex Intelligence) strongly preferred. Hands-on experience building LLM-based applications including prompt engineering RAG implementations and natural language interfaces for structured and unstructured data Strong SQL proficiency and experience working with complex enterprise data models. You understand what makes semantic layers work. Consulting agency or client-facing delivery experience preferred. Youre comfortable owning a client relationship and navigating ambiguity. Production experience with evaluation frameworks quality measurement and continuous improvement processes for AI systems Qualifications: Education: Bachelors degree in a quantitative field (Computer Science Statistics Mathematics Engineering or related); Masters degree preferred Technical Credibility: Strong Python skills and software engineering fundamentals Expert-level SQL and experience with query optimization data modeling and semantic layer design Familiarity with AI evaluation methodologies including accuracy measurement reliability testing and continuous improvement frameworks for LLM-based systems Experience with cloud platforms (Snowflake Databricks AWS Azure GCP) and modern data infrastructure; comfort working across client tech stacks Understanding of LLM capabilities/limitations RAG architectures and agentic frameworks Leadership & Communication: Proven ability to lead delivery teams and drive technical decisions while keeping clients informed and aligned Excellence in technical storytelling and translating complex AI system behavior into business terms Strong presentation skills with ability to engage executives and practitioners in the same conversation Experience navigating ambiguity and making trade-off decisions in client-facing environments Additional Assets: Experience building evaluation frameworks and golden datasets for AI/LLM systems Background in marketing analytics customer insights or business intelligence Experience with both structured data (SQL data warehouses) and unstructured data (documents text) pipelines Published work or presentations on AI/ML topics Certifications in Databricks Snowflake or cloud platforms What Success Looks Like: In this role youll be measured on your ability to lead teams that deliver production-ready AI Analytics systems meeting our high standards for quality reliability and client satisfaction. For knowledge extraction and insights generation implementations this includes achieving high accuracy and reliability metrics while ensuring clients can own and evolve these systems independently. Clients will see you as their trusted technical advisor. Someone who can challenge their thinking explain whats possible and deliver solutions in their environment that theyre equipped to maintain. Your teams will grow under your leadership and your engagements will become reference cases for the practice. Success includes establishing repeatable delivery methodologies advancing our AI evaluation capabilities and helping position Merkles Analytics Applied AI Practice as a go-to partner for applied AI in the analytics space.

Additional Information

The anticipated base salary range for this position is $113000 - $182850. Placement within the salary range is based on a variety of factors including relevant experience knowledge skills and other factors permitted by law.

Benefits available with this position include:

Medical vision and dental insurance

Life insurance

Short-term and long-term disability insurance

401k

Flexible paid time off

At least 15 paid holidays per year

Paid sick and safe leave and

Paid parental leave.

Dentsu also complies with applicable state and local laws regarding employee leave benefits including but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act in accordance with its plans and policies. For further details regarding Dentsu benefits please visit .

To begin the application process please click on the Apply button at the top of this job posting. Applications will be reviewed on an ongoing basis and qualified candidates will be contacted for next steps. #LI-RB1 #LI-Hybrid #LI-Merkle

At dentsu we believe great work happens when were connected. Our way of working combines flexibility with in-person collaboration to spark ideas and strengthen our teams. Employees who live within a commutable distance of one of our hub offices currently located in Chicago metro Detroit Los Angeles and New York City are required and expected to work from the office three days per week (two days per week for employees based in Los Angeles). Dentsu may designate other Hub offices at any time. Those who live outside a commutable range may be designated as remote depending on the role and business needs. Regardless of your work location we expect our employees to be flexible to meet the needs of our Company and clients which may include attendance in an office.

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