• Work on training and evaluating models and prompts, fine-tuning, optimization of chunking and tokenization, bias detection, adversarial prompt testing, and selection of embeddings (supporting RAG); • Train and evaluate generative AI models, including LLMs and multimodal models; • Develop and optimize prompts, including adversarial testing and risk mitigation; • Perform fine-tuning and hyperparameter tuning to maximize performance; • Implement chunking and tokenization strategies for efficiency and quality; • Detect and remediate biases in data and models, ensuring ethical compliance; • Select and validate embeddings for RAG (Retrieval-Augmented Generation) applications; • Monitor quality, robustness, and safety metrics for models; • Collaborate as a subject-matter specialist with engineers and architects to securely integrate models into production pipelines.

• Own revenue predictability, planning, and executive insight across new, renewal, and expansion revenue. • Manage and coach a Revenue Insights Analyst focused on post-sales analysis; hire and scale the team as scope grows • Own pre-sales analytics and planning personally while overseeing team output and quality • Own forecast methodology and accuracy across all revenue streams • Lead forecast cadence and executive performance reviews • Build and manage capacity models (headcount, coverage, productivity) • Lead annual and quarterly planning processes; integrate pipeline signals with planning assumptions • Lead quota and territory planning processes, ensuring capacity, coverage, and quota assumptions are aligned and data-backed • Translate performance data into actionable insight, including CAC, sales effectiveness, and full-funnel conversion/velocity across new, renewal, and expansion • Proactively flag performance risks and pipeline gaps early - before quarter-end - with clear recommended actions • Deliver executive and Board-level reporting • Build and maintain pipeline reporting (coverage, conversion, progression, aging) • Support forecast process (rollups, validation, scenarios) • Track leading indicators (pipeline creation, early-stage conversion) • Produce weekly forecast packages and dashboards • Ensure data accuracy and reporting consistency • Implement approaches to apply AI to streamline forecast modeling and scenario generation • Use AI-driven anomaly detection to surface pipeline/forecast risk earlier • Leverage AI to automate draft narratives and insights, freeing time for judgment-level analysis

Role Description This role will give you the opportunity to work on high added value data governance and data quality projects, building robust data management frameworks for our clients within a growing service company. As our Data Governance Specialist, you will help clients take control of their data assets — defining policies, enforcing quality standards, managing metadata, and deploying governance tooling. You will collaborate closely with data engineers, analysts, and client stakeholders to embed governance practices across the full data lifecycle. What will you do? - Design, implement, and operationalize data governance frameworks across client engagements, covering the following areas: - DATA GOVERNANCE & POLICY - Define and implement data governance frameworks, policies, and standards tailored to client environments. - Establish data ownership, stewardship models, and accountability structures across business and technical teams. - Develop and maintain data dictionaries, business glossaries, and classification taxonomies. - Ensure compliance with data regulations and internal data management policies (GDPR, BCBS 239, etc.). - DATA QUALITY & LINEAGE - Design and implement data quality rules, profiling routines, and monitoring dashboards. - Investigate and remediate data quality issues across structured and unstructured data sources. - Map and document end-to-end data lineage to support auditability and impact analysis. - Define and track data quality KPIs and SLAs in collaboration with data owners. - METADATA & CATALOGUING - Deploy and administer data catalog and metadata management tools (e.g. Informatica, Collibra, Alation, Microsoft Purview). - Enrich metadata assets with business context, ownership, sensitivity classification, and usage information. - Drive adoption of the data catalog across business and technical teams. - TOOLING & INTEGRATION - Configure and operate data governance platforms, primarily Informatica (IDMC, Axon, EDC, DQ) and equivalent tools. - Integrate governance tooling with existing data pipelines, warehouses, and BI environments. - Automate data quality checks and governance workflows within ETL/ELT pipelines. - OTHER - Provide internal training and knowledge-sharing sessions on data governance best practices. - Support the Team Lead/Manager on client relationships, business development, and internal projects. Qualifications - Master’s degree in a relevant field such as Computer Science, Information Systems, Data Management, Statistics, or Applied Mathematics. - Full proficiency in French and English. - 3 to 6 years of experience in data governance, data management, or data engineering with a strong governance focus. - Experience working in a consulting, financial services, or multi-client environment is a plus. Requirements - TECHNICAL SKILLS - DATA GOVERNANCE TOOLS - Proven hands-on experience with Informatica (IDMC / Intelligent Data Management Cloud, Axon Data Governance, Enterprise Data Catalog, Data Quality). - Experience with other governance and cataloguing platforms such as Collibra, Alation, Ataccama, or Microsoft Purview. - Familiarity with data quality tools: Great Expectations, Monte Carlo, Soda, or equivalent. - DATA ENGINEERING & QUERYING - Solid experience with SQL for data profiling, querying, and quality rule implementation across relational databases and data warehouses (Snowflake, BigQuery, Synapse, Redshift). - Experience in Python for automating data quality checks, metadata extraction, and governance workflows. - Understanding of ETL/ELT pipelines and ability to embed governance controls within them (dbt, Airflow, Informatica PowerCenter/IDMC). - DATA ARCHITECTURE & PLATFORMS - Good understanding of data platform architectures: data lake, lakehouse, and data warehouse environments. - Familiarity with cloud platforms and their native governance services: Azure Purview, AWS Glue Data Catalog, Google Dataplex. - Understanding of data modelling concepts and their impact on governance (dimensional modelling, data vault, etc.). - STANDARDS & COMPLIANCE - Knowledge of data governance frameworks and standards: DAMA-DMBOK, BCBS 239, GDPR, ISO 8000. - Experience defining and applying data classification schemes (sensitivity labels, PII tagging, retention policies). - Exposure to master data management (MDM) concepts and tools is a plus. - INTERPERSONAL SKILLS - Ability to engage and influence both technical teams and business stakeholders on data governance topics. - Strong analytical mindset with the ability to diagnose data quality issues and translate them into actionable remediation plans. - Good communication skills with the ability to document governance frameworks clearly and present findings to senior audiences. - Detail-oriented, rigorous, and comfortable working across multiple client contexts simultaneously. Benefits - A competitive salary. - A great working environment. - A steep learning curve with interesting and diverse topics to work on. - A healthy work-life balance. - Health insurance benefits. Company Description Infomineo is an equal opportunity employer, we prohibit any sort of discrimination (based on color, race, sex, sexual orientation, religion, national origin or any other attributes) in all aspects of employment (recruiting, hiring, wages and salary, promotions, benefits, training and job termination). If you believe you match our requirements and values, we would be happy to hear from you. Visit our website to know more about us, our services and company culture.

Role Description We are looking for a Tableau expert who lives and breathes dashboards, visualizations, and analytics. This role is focused almost exclusively on Tableau development and reporting. The ideal candidate can turn complex datasets into intuitive, high-performance dashboards that help drive business decisions. The Tableau Developer will be responsible for designing, building, optimizing, and maintaining Tableau dashboards used across the organization. They will work closely with business stakeholders, product teams, and data teams to transform requirements into impactful visual analytics. This is a hands-on role for someone who enjoys solving complex reporting challenges and creating exceptional user experiences within Tableau. - Design, develop, and maintain Tableau dashboards and reports. - Create interactive visualizations that communicate complex data clearly. - Build and maintain calculated fields, parameters, sets, filters, and Level of Detail (LOD) calculations. - Optimize dashboard performance and improve load times. - Develop reusable Tableau data sources and reporting frameworks. - Work with stakeholders to gather requirements and translate business questions into dashboards. - Validate data accuracy and ensure reporting consistency. - Troubleshoot dashboard issues and support Tableau users across the organization. - Establish and maintain Tableau development standards and best practices. - Document dashboards, calculations, and reporting logic. Qualifications - 3+ years of hands-on Tableau development experience. - Advanced knowledge of Tableau Desktop and Tableau Cloud/Server. - Strong expertise in: - Calculated Fields - LOD Expressions - Parameters - Sets - Dashboard Actions - Performance Optimization - Tableau Data Modeling - Experience building executive-level dashboards and KPI reporting. - Strong analytical and problem-solving skills. - Ability to work independently and manage multiple reporting projects simultaneously. - Excellent communication skills and stakeholder management. Requirements - Experience with large datasets and complex reporting environments. - Familiarity with Tableau extracts, Hyper files, and performance tuning. - Basic SQL skills. - Experience with data warehouses such as BigQuery, Snowflake, PostgreSQL, or SQL Server. - Experience with Tableau governance, permissions, and deployment processes. What Success Looks Like - Dashboards are fast, intuitive, and trusted by users. - Business stakeholders can answer key questions without manual analysis. - Tableau becomes the primary analytics interface across the organization. - Reporting is standardized, scalable, and well documented. - New dashboards are delivered quickly with high quality and minimal rework.