Lead and advance the Integrated Business Planning (IBP) process across commercial, operations, and finance functions to drive enterprise decision-making and performance.
Compensation
A reasonable estimate of the current starting annual base salary for this position is $170,000 - $190,000.
Responsibilities
Own and facilitate the rolling 36‑month IBP process
Facilitate monthly cycle across Product/Portfolio Review, Demand Review, Supply Review, Integrated Reconciliation, and Management Business Review
Advance standards, decision rights, inputs, outputs, KPIs, and meeting effectiveness
Govern the IBP maturity roadmap and 2027 priorities
Partner with functional owners to define preparation, analysis, recommendations, presentation, and follow‑through
Requirements
Bachelor’s degree in Business, Supply Chain, Finance, Strategy, or related field
Nice to have: Master’s degree
Nice to have: Experience in CPG or food manufacturing
Nice to have: Experience with 18–36 month planning horizons
A focused and passionate client Research Consultant to help drive business success across a variety of industries and global brands, turning human insights into clear stories, stronger decisions, and better customer experiences.
Compensation
The salary range for this role is CAD $65,000 to $85,000, with final compensation based on skills, experience, and internal equity.
Responsibilities
Assists all stages of the market research project cycle
Designing and developing questionnaires and discussion guides
Overseeing data collection & ensuring strict quality control
Identifying and writing up analytical findings
Visualizing and reporting quantitative and qualitative findings
Requirements
University or College degree in a relevant discipline
Nice to have: Sophisticated market research practices
Nice to have: Quantitative market research methods
Data Engineers work closely with business stakeholders to understand their goals and identify data-driven strategies to achieve those goals. They design data modeling processes, create algorithms and predictive models to extract the insight the business needs and help analyze the data to increase the productivity and efficiency of the business.
Responsibilities
Expertise working experience with programming languages like Python, and SQL
Solid understanding of data lake, data warehousing and analytics
Research, design, and implement data modeling designs to solve complex problems
Communicate complex concepts and data pipelines to non-technical audiences through data visualizations
Performs statistical analysis and using results to improve models
Design, implement and scale governance processes for new generative and agentic AI models and launches related to Frontier Safety, partnering with cross‑functional teams and providing leadership with risk evaluations and readiness plans.
Locations (2)
Washington D.C., District of Columbia, United States
Design, implement and scale governance processes for new generative and agentic AI models and launches related to Frontier Safety.
Act as a trusted partner to executive stakeholders, building strong relationships and providing clear, compelling communications on complex trust and safety issues.
Partner with cross‑functional teams, including product, engineering, and research, to embed safety and trust‑oriented processes and technologies directly into the model and product development lifecycle.
Design and execute sophisticated data analyses to identify emerging risks, measure the effectiveness of our mitigations, and inform strategic decisions.
As part of the Global People Analytics & Governance team, you will help turn HR data into forward-looking insights that support workforce and business decisions. You will contribute to predictive and scenario-based workforce analytics, enrich strategic dashboards, and help shape data and AI use cases that anticipate future skills, capacity, retention, and organisational needs.
Responsibilities
Produce monthly and quarterly HR reports
Consolidate global HR metrics and workforce indicators
Develop forward-looking workforce analyses, including trends, forecasts and scenarios, to anticipate future skills, capacity, attrition and organisational needs
Support recurring workforce analyses
Check data consistency and quality before publication
Requirements
Master’s degree (Bac+4/Bac+5) in Data Analytics
Master’s degree (Bac+4/Bac+5) in Business Analytics
Master’s degree (Bac+4/Bac+5) in Data Science
Master’s degree (Bac+4/Bac+5) in Statistics
Master’s degree (Bac+4/Bac+5) in Information Systems
Turn complex data into strategic insights that help shape Sephora’s Omni, Digital, and Retail business, uncovering client behaviors and measuring program performance across digital and store channels.
Compensation
The annual base salary range for this position is $119,840.00 - $134,820.00 Individuals employed in this position may also be eligible to earn bonuses.
Responsibilities
Partner independently with stakeholders to support key Omni Convenience initiatives, delivering strategic analyses, channel performance insights, forecasting, and analytics guidance that inform business decisions.
Build and maintain accurate, intuitive, and actionable dashboards and reports that give business partners clear visibility into program performance, trends, and opportunities.
Conduct ad hoc analyses to answer strategic business questions, uncover actionable insights, and troubleshoot data or performance issues.
Translate complex data and digital client journey insights into compelling narratives and recommendations that help influence decision-making across the organization.
Leverage AI, automation, and emerging technologies to enhance analytics communications, streamline reporting and dashboards, simplify complex analyses, and scale data-driven decision-making.
Requirements
Bachelor’s degree in Business, Analytics, Mathematics, Statistics, or a related field
Nice to have: R
Nice to have: Python
Nice to have: Adobe Analytics
Data Scientist, Senior - DPAE Maritime M & S
Morgan Business Consulting, LLC · Posted Nov 14, 2026
Senior Data Scientist to support the US Navy’s surface ship modernization and sustainment efforts.
Locations (2)
Arlington, Virginia, United States
United States
Responsibilities
Assist with design, development, and validation of advanced statistical and machine learning models supporting Navy operation and business functions
Conduct exploratory data analysis on large, complex and often unstructured datasets from multiple Navy information systems
Architect robust Qlik Sense data model application utilizing complex Load Scripting and Data Transformation (ETL) to ingest and normalize 5,000+ daily Casualty Reports (CASREPs) from disparate sources into an associative engine
Develop variable-driven logic and nested If/Match functions to parse plain-language CASREP severity, mapping text to a quantitative 4-tier RAGB (Red, Amber, Green, Black) status for warfare area visualization
Engineer advanced Set Analysis expressions within Master Items to calculate dynamic day-over-day deltas and Casualty Correction (CASCOR) percentages, providing automated trend reporting
Apply industrial engineering principles, data modeling, and data cleansing to optimize manufacturing workflows and systems, collecting, warehousing, and visualizing key production metrics.
Responsibilities
Design, implement, and maintain data collection pipelines and warehousing workflows across manufacturing systems
Develop automated data cleansing procedures and data validation frameworks to ensure high fidelity in operational metrics
Build clear, intuitive data visualizations and reporting dashboards to communicate equipment, cycle time, and production trends
Apply industrial and manufacturing engineering methodologies to analyze bottlenecks and optimize floor operations
Utilize SQL, Python, and related tools to perform root-cause analyses and model complex operational problems
Requirements
Bachelor’s degree in Industrial Engineering
Bachelor’s degree in Manufacturing Engineering
Bachelor’s degree in Production Operations Management (POM)
Designing and developing advanced AI/ML solutions to solve complex business problems.
Responsibilities
Demonstrates proficiency in designing, developing, and deploying machine learning models to address complex analytical problems.
Represents the team in cross-functional engagements with business, engineering, and analytics stakeholders, providing technical leadership in AI solution design and implementation.
Applies extensive technical knowledge to develop and maintain scalable data pipelines and ML workflows across modern data platforms.
Applies organizational and third-party technologies to build complex AI-driven solutions, independently implementing end-to-end pipelines from data ingestion to deployment.
Integrates technical expertise with business understanding to deliver impactful insights, collaborating with stakeholders to translate model outputs into actionable outcomes.
Requirements
Four-year or Graduate Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or any related discipline; or equivalent work experience.
Nice to have: Microsoft Azure AI Engineer Associate / Data Scientist Associate
Nice to have: Databricks or equivalent platform certifications
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