ARTIFICIAL INTELLIGENCE CONSULTANT JOB DESCRIPTION

An AI Consultant who cannot translate model outputs into executive decisions leaves a CoE investment without a business case. This role owns the full arc from opportunity identification through production monitoring, ensuring that AI and machine learning initiatives move from pilot to measurable value realization. Engagements span regulated industries, financial services, insurance, and leasing, where data governance mandates and stakeholder scrutiny demand more than technical competence. Credibility here is earned in the boardroom as much as in the model pipeline.

As the Artificial Intelligence Consultant, you are accountable for scoping, designing, and delivering end-to-end AI and ML solutions that convert enterprise data assets into quantified business outcomes across client or internal lines of business. You work within a cross-functional Center of Excellence or consulting engagement structure, collaborating with business stakeholders, data engineering, and operations teams while reporting to a CoE lead or principal consultant.

Career Impact: Delivering AI solutions across financial services, insurance, and leasing builds a portfolio of regulated-domain deployments that distinguish you from practitioners without enterprise compliance exposure.

Business Impact: The models and pipelines you put into production directly determine whether a line of business achieves its AI-enabled revenue or efficiency targets, or misses them and resets.

Growth Opportunity: Progressing from consultant to senior consultant or ML architect becomes achievable as you accumulate cross-functional delivery experience and Scrum Master credentials recognized across enterprise engagements.

• Design and implement end-to-end AI and ML architectures supporting analytical models, data pipelines, and BI reporting across enterprise environments.
• Identify high-value AI opportunities within business and operations functions, then translate findings into scoped, stakeholder-approved delivery plans.
• Monitor live AI models in production and training environments to validate business value realization against defined targets.
• Partner with data engineering and platform teams to automate data ingestion, retention, and archiving in compliance with data governance policies.
• Present solution recommendations and implementation roadmaps to senior business and IT stakeholders, articulating complex AI concepts in accessible terms.
• Facilitate Agile ceremonies including backlog prioritization, sprint planning, and retrospectives as Scrum Master or active participant.
• Validate technological readiness and data availability before solution commitments are made to clients or internal sponsors.
• Capture and standardize best practices for building, maintaining, and monitoring responsible AI deployments across the organization.

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent work experience.
• 4 or more years of AI, machine learning, or advanced analytics experience, with demonstrated delivery in enterprise or consulting environments.
• Experience designing and deploying machine learning models and data pipelines using Python, R, or Scala in production settings.
• Proficiency in both relational and non-relational data store environments, including SQL-based and Big Data platforms.
• Working knowledge of data governance principles including data quality, metadata management, and compliance-aligned ingestion practices.
• Experience applying Agile methodologies, including Scrum ceremonies, in multi-stakeholder project delivery.
• Strong verbal and written communication skills with the ability to present AI findings and recommendations to non-technical executive audiences.

• Graduate degree in Artificial Intelligence, Machine Learning, Computer Science, or a closely related discipline.
• Prior experience at a Big 4 or major MNC consulting firm, or equivalent delivery in a regulated-industry CoE environment.
• Scrum Master certification or demonstrated experience facilitating product backlog management across cross-functional analytics teams.
• Domain experience in at least one of the following: financial services, insurance, leasing, or life sciences, particularly where compliance or model governance requirements apply.

• Business value realization rate, measuring the percentage of deployed models meeting their defined LOB outcome targets.
• Model uptime and production stability rate, reflecting the reliability of AI solutions under live business conditions.
• Time from pilot approval to production deployment, tracking delivery efficiency across the engagement lifecycle.
• Stakeholder-reported solution adoption rate, capturing how consistently deployed AI tools are integrated into business workflows.
• Sprint velocity and backlog completion percentage, indicating delivery consistency across Agile-managed project phases.
• Typical tools: Big Data platforms (commonly Spark, Hadoop); ML frameworks (commonly Python-based stacks, Databricks); project tracking (commonly Jira or Azure DevOps).

• Base Salary Range: $120,000 to $165,000 annually, depending on seniority and industry
• Bonus: Performance-based bonus, typically 10% to 20% of base salary
• Equity: Rare in consulting; RSUs or profit-sharing offered at senior levels in some firms
• Health Benefits: Medical, dental, and vision coverage; employer contribution standard
• PTO: 15 to 20 days annually; some firms offer unlimited PTO at senior levels
• Common Perks: Learning platform access, conference sponsorship, certification reimbursement

Figures are estimates based on general US market benchmarks and may be outdated. Adjust based on location, company size, and seniority level.

Background check completion, including verification of employment history and, where applicable, credit history relevant to financial services engagements, is a condition of employment. All qualified applicants are considered without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, or local law. Reasonable accommodations for individuals with disabilities are available upon request throughout the hiring process. Candidates must be authorized to work in the United States.

Reporting to platform leadership, the Artificial Intelligence Consultant owns end-to-end AI solution delivery across all lines of business while managing data ingestion, retention, and archiving under governance policy. Partnering with data scientists and cross-functional business and operations teams, the consultant identifies key issues and recommends AI-enabled solutions that drive measurable business value.

Key Responsibilities

• Manage end-user onboarding and offboarding activities on all platforms.
• Provide, streamline, and automate data ingestion, data retention, and archiving while adhering to data governance policies and procedures.
• Serve as the single point of contact to remedy all platform issues for data scientists.
• Help streamline current processes and move toward self-service activities on on-premise and future cloud platforms.
• Uphold effective and optimal platform experience.
• Continuously measure and improve platform health.
• Support live AI models in production and in training environments supporting business soft-launch pilots, and monitor business value realizations.
• Analyze cross-functional teams in business and operations that require broad impact and act as a key participant in evaluation.
• Participate in business strategy to recommend and deliver AI-enabled solutions that solve business challenges.
• Perform technological readiness, data availability, and resource assessments required to execute proposed solutions.
• Present recommendations to drive implementation of initiatives and programs.
• Identify key issues that may arise during development or implementation.
• Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals.

Required Qualifications

• 2+ years of AI solutions experience, or equivalent demonstrated through work experience, training, military experience, or education.
• 2+ years of experience in strategic planning, initiative management, or project management.
• Experience with design, implementation, and governance of AI, NLP, or machine learning architecture.
• Knowledge and understanding of big data environments, including Hadoop.
• Experience with Waterfall and Agile project methodologies, including Scrum and Kanban.
• Strong communication skills with the ability to articulate complex material to a diverse audience.
• Strong teamwork and interpersonal skills.
• Strong problem-solving skills with the ability to work under pressure and tight project timelines.

Embedded within a client-facing consulting practice, the Artificial Intelligence Consultant applies emerging technologies to design data structures and analytical models that turn client data into actionable business outcomes across BI, DW, and big data solutions. Working closely with industry stakeholders through every phase of the project lifecycle, from strategy and scoping to deployment, the consultant links business requirements to recommended analytics and platform models that deliver measurable client value.

Key Deliverables

• Apply emerging technologies to help clients maximize the value of their data by generating actionable insights that provide real business outcomes.
• Design and implement data structures to support big data, analytical models, and traditional BI/DW reporting solutions.
• Design and develop data integration using data governance, data quality, MDM, and metadata management.
• Apply analytical models to predict business outcomes using tools such as DataRobot and languages such as Python or R.
• Link industry-specific business requirements to BI, analytics, and big data solutions.
• Recommend BI/DW/analytics processes, governance, organizational and platform models, tool selections, and data integration options to clients.
• Deliver project experience through all phases of the project lifecycle, from strategy and advisory, scoping and planning, requirements gathering, design, development, testing, training, and deployment.

Skills & Qualifications

• A good honors degree, preferably at postgraduate level, in Computer Science, Software Engineering, Statistics, Mathematics, or a related discipline.
• Minimum 4 years (Consultant) or 6 years (Senior Consultant) of relevant experience.
• Experience in a Big 4 or MNC consulting firm or industry-equivalent role.
• Demonstrated experience across a broad range of industries, including energy and resources, public sector, financial services, life sciences and healthcare, manufacturing, or telecommunications.
• Strong experience in one or more programming languages, including Scala, Python, or R.
• Experience with one or more non-relational data stores such as Pivotal, Cloudera, Hortonworks, MapR, or Oracle BDA.
• Experience with one or more relational data stores using SQL, Oracle DB, Microsoft SQL Server, IBM Netezza, Teradata, or MySQL.
• Experience building data ingestion and transformation pipelines using big data technologies, including Spark, Hive, Pig, Kafka, MapReduce, HBase, Sqoop, Flume, or Storm.
• Experience with technologies such as Microsoft SQL, Oracle, SAP, Cloudera, MuleSoft, Qlik Technologies, or Informatica.
• Experience working with Agile software engineering tools and source control management tools such as Git, Subversion, or Mercurial.
• General knowledge of Linux/Unix-based operating systems and shell scripting.
• Experience directly interfacing with business and IT stakeholders.
• Excellent communication and presentation skills in English.

Reporting to the business and analytics leadership team, the Artificial Intelligence Consultant partners with stakeholders to identify innovative AI opportunities and standardize cutting-edge analytics services across current processes and systems. Partnering with cross-functional teams in analytics, product management, and operations, the consultant acts as Scrum Master to prioritize the product backlog while promoting best practices for building, maintaining, and monitoring responsible AI.

Primary Duties

• Act as an AI ambassador and create awareness about the latest AI capabilities to facilitate the translation of AI into business value.
• Identify innovative AI opportunities to support the business and realize them together with stakeholders.
• Deliver cutting-edge analytics services to stakeholders and standardize and effectively deploy these in current processes and systems.
• Capture and promote best practices for building, maintaining, and monitoring effective and responsible AI.
• Act as Scrum Master to ensure effective product backlog prioritization.
• Contribute actively to creating an innovative and inspiring working environment.

Required Qualifications

• Advanced degree in computer science, econometrics, mathematics, applied statistics, or an engineering discipline, with a graduate degree in AI, machine learning, or equivalent self-study and experience preferred.
• 1+ years of industry experience using machine learning to solve real-world problems with large datasets.
• Experience extracting data from various databases and analyzing large datasets for conversion into useful business information.
• Experience building and deploying AI/ML models, building data and model pipelines, and designing model monitoring solutions.
• Experience working with Scrum, with Scrum Master experience a plus.
• Experience with data analytics and DevOps tools such as Databricks and Azure DevOps, with knowledge of Docker, CI/CD, and Kubernetes a plus.
• Demonstrable knowledge of modern programming languages such as Python or other AI/ML languages, with SQL, YAML, and Spark a plus.
• Strong AI literacy and ability to describe and convey complex AI concepts effectively.
• Experience collaborating across multiple cross-functional teams, including analytics, product management, and operations.