Consultant, Data Analytics & Reporting-Food

Staff Electrical Engineer (Global Facilities Engineering)

Staff Engineer, Electrical – Global Facilities Engineering

Forward Deployed AI Strategist

Sales Operation Analyst

Commercial Finance Manager

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Manager, Data Engineering

Accounts Receivable (6 Months Contract)

Responsibilities: <ul><li>Data Analysis: Collects, transforms, and analyzes data from multiple sources to identify trends, patterns, anomalies, and actionable insights that support reporting, performance tracking, and decision making.</li><li>Reporting &amp; Visualization: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.</li><li>Data Modeling &amp; Automation: Supports data models, reporting logic, and workflow automation, while identifying and implementing opportunities to improve data collection and reporting processes using standard data management and reporting practices.</li><li>Advanced Analytics Awareness: Familiarity with predictive analytics, AI/ML, and data science concepts to support evolving analytics solutions.</li><li>Data Quality &amp; Requirement Support: Validates data, supports reporting requirements, and helps ensure the accuracy and consistency of analytics solutions.</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field such as Data Science, Statistics, Computer Science, Business Analytics, or a related discipline, or equivalent practical experience.&nbsp;</li><li>Minimum of 3-4 years of relevant work experience in data analytics, reporting, or business intelligence roles.</li><li>Strong skills in analyzing data and translating reporting needs into effective analytics solutions and insights.</li><li>Very strong skills in Power BI and data visualization.</li><li>Proficiency in SQL, Excel, Power Query, and related tools such as VBA or Python for analysis, modelling, and visualization.</li><li>Working knowledge of data warehousing, data lakes, and cloud data platforms such as Snowflake or AWS.</li><li>Experience automating workflows and building low-code solutions using Power Platform tools such as Power Automate and Power Apps.</li><li>Familiarity with (predictive) analytics, AI/ML and data science.</li><li>Business understanding and financial acumen to interpret data and generate practical insights.</li><li>Comfortable working in agile ways of working, managing multiple priorities, and contributing effectively both independently and in a team environment.</li></ul>

Responsibilities: <ul><li>Act as a Subject Matter Expert (SME) for electrical systems across global facilities.</li><li>Develop and govern global engineering standards, specifications, and BKMs.</li><li>Lead design reviews, ensuring alignment with global requirements and best practices.</li><li>Drive improvements in system reliability, cost efficiency, and maintainability.</li><li>Support large-scale design and construction projects globally.</li><li>Conduct system studies, capacity analysis, and performance evaluations.</li><li>Collaborate with cross-functional stakeholders to align engineering solutions.</li></ul> Requirements: <ul><li>Bachelor’s Degree in Electrical Engineering or equivalent.</li><li>10–13 years of relevant experience in semiconductor or industrial facilities.</li><li>Strong expertise in electrical distribution systems (HV/MV/LV).</li><li>Experience with critical systems (UPS, generators, sag mitigation).</li><li>Proficiency in system modeling, analysis, and reliability engineering.</li><li>Experience in design review and construction project support.</li></ul>

Responsibilities: <ul><li>Act as a Subject Matter Expert (SME) for electrical systems across global facilities.</li><li>Develop and govern global engineering standards, specifications, and BKMs.</li><li>Lead design reviews, ensuring alignment with global requirements and best practices.</li><li>Drive improvements in system reliability, cost efficiency, and maintainability.</li><li>Support large-scale design and construction projects globally.</li><li>Conduct system studies, capacity analysis, and performance evaluations.</li><li>Collaborate with cross-functional stakeholders to align engineering solutions.</li></ul> Other Responsibilities: <ul><li>Lead root cause analysis for major system issues.</li><li>Mentor junior engineers and guide technical development.</li><li>Support sustainability and energy optimization initiatives.</li></ul> AI Responsibilities <ul><li>Leverage AI tools to enhance data analysis, predictive maintenance, and engineering insights.</li><li>Promote adoption of AI-enabled solutions within engineering workflows.</li></ul> Requirements: Minimum Required Qualifications/Experience: <ul><li>Bachelor’s Degree in Electrical Engineering or equivalent.</li><li>10–13 years of relevant experience in semiconductor or industrial facilities.</li></ul> Must Have Technical Skills: <ul><li>Strong expertise in electrical distribution systems (HV/MV/LV).</li><li>Experience with critical systems (UPS, generators, sag mitigation).</li><li>Proficiency in system modeling, analysis, and reliability engineering.</li><li>Experience in design review and construction project support.</li></ul> Must Have Soft Skills: <ul><li>Strong leadership and influencing skills.</li><li>Excellent communication and stakeholder management.</li><li>Ability to prioritize and drive multiple initiatives concurrently.</li><li>Strategic problem-solving capability.</li><li>AI Requirements</li><li>Ability to leverage AI tools for engineering analysis, operational improvements, and reporting.</li><li>Highly Desirable / Preferred</li><li>Experience leading regional/global engineering initiatives.</li><li>Knowledge of sustainability programs and green infrastructure.</li><li>Professional Engineer (PE) certification or equivalent.</li></ul>

Role Description: <ul><li>The Strategy team is looking for a hands-on AI-enabled strategy and market intelligence professional to materially accelerate the way we conduct deep research, market intelligence, analytical modeling, and GTM analysis by applying high impact AI workflows and translating them into sharper strategic decisions.</li><li>The individual will partner with business, product, commercial, and tech teams to translate ambiguous questions into actionable insights, while developing and scaling AI-enabled solutions that improve strategic decision-making and drive measurable business impact.&nbsp;</li><li>The individual is expected to work in close partnership with our client IT team, to leverage existing AI &amp; data capabilities on Databricks &amp; AWS (where applicable) while developing solutions.</li></ul> Responsibilities: Strategic problem solving and driving cross-functional execution&nbsp; <ul><li>Translate AI-assisted analyses into practical executive decisions by applying strong business judgment, rigorous validation protocols, and a sharp “so-what” orientation</li><li>Collaborate with and influence senior stakeholders across strategy, sales, technology teams, and P&amp;L owners</li><li>Good first-principles and problem-solving capabilities with the ability to build and test strategic hypotheses Identifying meaningful opportunities to leverage AI and deploying scaled AI solutions at pace</li></ul> Identify, assess, and prioritize high-value AI and automation opportunities by translating business challenges into scalable, practical solutions&nbsp; <ul><li>Design proprietary AI-enabled workflows, agents, and accelerators for recurring strategy activities (competitor monitoring, earnings call tracking, tariff and regulatory intelligence, voice-of-customer mining etc.)</li><li>Build reusable templates, workflows, and modules to drive adoption and embed AI capabilities into strategy processes</li></ul> Executing rapid AI-augmented research and competitive intelligence&nbsp; <ul><li>Lead AI-augmented research using tools like Claude, OpenAI, Perplexity, AlphaSense, CapIQ etc. to deliver source-triangulated competitive and industry insights</li><li>Synthesize structured datasets (S&amp;P Capital IQ, Bloomberg, IDC, Gartner) and unstructured sources (10-Ks, analyst reports, expert interviews) – to generate and validate AI-assisted outputs</li></ul> Support strategy team in day-to-day execution by leveraging AI-led tools <ul><li>Lead AI-enabled market sizing, opportunity mapping, and TAM/SAM/PAM modelling</li><li>Accelerate financial modelling – scenario and sensitivity analyses, valuation, NPV/IRR, segment P&amp;Ls, pricing</li><li>Support M&amp;A pipeline by AI-screening targets and generating investment theses</li></ul> AI enablement, coaching and continuous innovation <ul><li>Coach strategy team members on prompting techniques, research workflows, and AI-fluent execution</li><li>Scale AI adoption across Corporate Strategy through hands-on mentorship of beginner users</li><li>Stay current on agentic stacks, multimodal models, and deep research agents</li></ul> Requirements: Skillset and capabilities AI fluency and hands-on deployment orientation&nbsp; <ul><li>Working knowledge of GenAI patterns – LLM capabilities/limitations, prompt design, etc.</li><li>Proven ability to convert business problems into reusable AI workflows, tools, or accelerators</li><li>Builder mindset with experience prototyping AI solutions using frontier tools &amp; low-code platforms</li></ul> Analytics, modelling, and research excellence <ul><li>Strong modelling skills across TAM/SAM/PAM, scenarios, sensitivities, NPV/IRR, valuation etc.</li><li>Ability to synthesize structured datasets with unstructured sources</li><li>Research discipline – source triangulation and rigorous validation of AI outputs</li></ul> Strategic problem solving, communication, executive presence, and influence&nbsp; <ul><li>Sharp "so-what" orientation to translate AI outputs into practical executive decisions</li><li>Crisp written and verbal communication, with ability to frame board-ready narratives</li><li>Skill in explaining AI workflows and implications to both technical and non-technical audiences</li><li>Stakeholder management across strategy, commercial, data, and technology teams</li></ul> Ownership, and execution <ul><li>Independently own workstreams end-to-end – from framing through deployment</li><li>High bar for quality; never publishes unchecked AI outputs or unvalidated analysis</li></ul> Coaching and capability building&nbsp; <ul><li>Patience and ability to coach colleagues on prompting, research workflows, and source validation</li><li>Track record of building reusable playbooks – templates and training modules that scale adoption</li></ul> Passion, curiosity, and learning agility <ul><li>Deep passion for AI, tech, and industrial innovation, with curiosity to stay current on frontier tools</li><li>Entrepreneurial ownership mindset and drive to build a new AI-enabled strategy capability</li></ul> Qualifications:&nbsp; <ul><li>BE / B-Tech in Computer Science Engineering, Data Science or a related analytical field required; MBA, MS, M-Tech or equivalent advanced degree strongly preferred.</li><li>3–4+ years of experience in AI transformation, analytics, or AI-enabled business building. Prior Forward Deployed Engineer / Solutions Architect / Senior Data Scientist background preferred.</li><li>Experience in a top-tier strategy consulting firm, AI-native consulting team, analytics firm or corporate / product strategy team role strongly preferred.</li><li>Demonstrated experience building or deploying 0–1 AI solutions (not just experimenting), GenAI, analytics, automation, or workflow solutions in a business environment required.</li><li>Proficiency in Excel and PowerPoint required; Python or equivalent scripting capability strongly preferred. Experience with DevOps, CI/CD pipelines, and infra as code (e.g., Jenkins, Docker, Kubernetes) required.</li><li>Proficient in implementing AI platforms like AWS Bedrock, LangGraph, Crew AI, Glean etc.</li><li>Knowledge of enterprise data environments (esp. SAP, Databricks) or cloud platforms (esp. AWS) is a plus. Experience integrating AI systems with enterprise data platforms required.</li><li>Experience with LLM-powered solutions, RAG systems, agentic workflows, AI research tools, or AI-enabled knowledge manage</li></ul>

Responsibilities: <ul><li>Support performance analysis: Assist in conducting in-depth analysis across sales representatives, segments and territories.&nbsp;</li><li>You will help identify trends, pinpoint growth opportunities and diagnose execution gaps to support data-driven improvements.</li><li>Assist with compensation planning: Collaborate with sales operations, leadership and compensation teams.&nbsp;</li><li>You will help gather data and provide analysis for incentive and compensation plans that align with strategic goals and recognize high performance.</li><li>Contribute to quota planning: Support quota planning and development processes.&nbsp;</li><li>You will help with data reviews to ensure transparent and equitable business goals that reflect current market realities.</li><li>Maintain data hygiene: Assist in establishing and following protocols for data accuracy, consistency and security to support trustworthy decision-making across the commercial organization.</li><li>Provide dashboard and reporting support: Contribute to the design, build and maintenance of advanced dashboards and reports.&nbsp;</li><li>You will help ensure sales teams and senior leadership have access to actionable intelligence for business decisions.</li><li>Support market research efforts: Help conduct customer, market and competitor research.&nbsp;</li><li>You will assist in generating timely insights that guide commercial strategies and position company for long-term growth in a competitive market.</li><li>Assist with win/loss analysis: Help analyze deals won and lost to provide strategic insights on pricing.&nbsp;</li><li>You will support identifying drivers of sales outcomes and share recommendations for competitive approaches and sustainable growth.</li><li>Aid in forecast planning: Work with business leaders to support and improve sales forecast planning.&nbsp;</li><li>You will assist in integrating performance metrics, pipeline insights and external market trends to inform resource allocation.</li></ul> Requirements: <ul><li>Relevant educational background in data analytics, sales, revenue operations, marketing, finance, or a related field, including hands-on experience through coursework, projects, or internships.</li><li>Exceptional analytical skills with the ability to solve complex problems using clear and actionable data while translating into actionable business insights</li><li>Excellent communication skills, with the ability to clearly present data insights and recommendations to cross-functional teams and business leaders</li><li>Advanced Microsoft Excel skills, including experience with formulas, pivot tables, data modeling, and large dataset analysis</li><li>Strong organizational and project management skills, with the ability to manage multiple priorities and deadlines in a fast-paced environment</li><li>Deep commitment to ownership, continuous learning and taking proactive steps to improve business outcomes.</li></ul>

Responsibilities: <ul><li>Own Managerial P&amp;L planning and forecasting, delivering accurate and documented forecasts and budgets</li><li>Lead and own the India FP&amp;A calendar (cross functional view – connected with S&amp;OP and Regional timeline)</li><li>Accountable for managerial P&amp;L reporting in Campari group consolidation system.</li><li>Provide visibility on P&amp;L by SKU / brand / state / channel / customer down to GP and/or CAAP and by account.</li><li>Manage SG&amp;A in collaboration with functional leaders.</li><li>Provide clarity on business performance drivers and variations vs previous forecasts, Budget and prior years</li><li>Pilar of the S&amp;OP process, leading the Volume to value conversion and ensure consistency with commercial planning.</li><li>Provide management relevant and accurate analytics providing visibility on the R&amp;O and as such, enabling effective business decisions.</li><li>Secure integrity of the Depletions/sell out reporting by brand, by state, by channel.</li><li>Understand COGS variances in collaboration with regional supply chain finance team</li><li>Work in close collaboration with controlling team to secure DD and A&amp;P accruals accuracy, documentation and relevance at all time.</li><li>Support Revenue Optimization agenda, partnering commercial team to optimize revenue performance by customers/distributors/channel and maximize profitability.</li><li>Drive internal control &amp; operating efficiency of the promotional program and trade spend.</li><li>Support Key Account managers for trade terms negotiation, providing relevant analytics.</li><li>Develop standardized Value Chain supporting commercial team needs</li><li>Develop sound and reasonable business case for innovation/new product launch/footprint expansion</li><li>Drive ROI analysis for all key initiatives – maximization of investment, share learnings.</li><li>Continually work with functional teams to drive profitable growth and strive for continuous ongoing improvement.</li><li>Drive initiatives through increased focus on the effectiveness and profitability of sales spend and through the proactive identification of profit/growth opportunities.</li><li>Represent finance and challenge financial efficacy in key cross functional forums like Exec reviews, valuation meetings.</li><li>Develop tools to support cross functional team work and decision making and help improvement of internal processes.</li><li>Support projects led by group aiming at improving analytics and efficiencies across finance</li></ul> Requirements: <ul><li>8-10 years experience in commercial finance and FP&amp;A role. Ideally close working experience with sales and marketing/ supply chain in a commercial capacity, preferably in the liquor industry or FMCG.</li><li>Qualification – Chartered Accountant</li><li>Experience in Liquor industry preferred, FMCG essential</li><li>Advanced excel and strong power-point skills</li><li>SAP, Power BI, BPC&nbsp;</li></ul>

Responsibilities: <ul><li>Lead experimentation and model development for AI/ML solutions in legal products.</li><li>Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Proven experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Able to analyze large-scale legal datasets to extract insights and improve model performance.</li></ul>

Responsibilities: <ul><li>Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Education: Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Strong experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Strong foundation in statistics, modeling, and large-scale text processing.</li></ul>

Responsibilities: <ul><li>DATA &amp; ANALYTICAL SOLUTIONS: Oversees the development of data products and solutions using big data and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li><li>DATA PIPELINES: Develops and monitors streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.</li><li>DATA SYSTEMS: Reviews existing data systems and architectures to lead identification of areas for improvement and optimization.</li><li>DATA INFRASTRUCTURE: Oversees the preparation of data infrastructure to drive the efficient storage and retrieval of data.</li><li>DATA FORMATS: Reviews and resolves appropriate data formats to improve data usability and accessibility across the organization.</li><li>STAKEHOLDER MANAGEMENT: Partners collaboratively with multi-functional data and advanced analytic teams to capture requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li><li>DATA FRAMEWORKS: Builds complex prototypes to test new concepts and provides guidance to implement data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li><li>AUTOMATED DEPLOYMENT PIPELINES: Oversees the development of automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li><li>DATA MODELING: Guides the team to perform data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li><li>TEAM MANAGEMENT: Manages team members to achieve the organizations goals, by ensuring productivity, communicating performance expectations, creating goal alignment, giving and seeking feedback, providing coaching, measuring progress and holding people accountable, supporting employee development, recognizing achievement and lessons learned, and developing enabling conditions for talent to thrive in an inclusive team culture.</li></ul> Requirements: <ul><li>Some experience in React, including hooks, context API, and state management libraries (Redux, Zustand)</li><li>Solid experience with JavaScript (ES6+), TypeScript, HTML5, CSS3.</li><li>Strong experience with C# and .NET Framework/.NET Core.</li><li>Solid understanding of object-oriented programming.</li><li>Experience with unit testing and mocking frameworks (e.g., xUnit, NUnit, Moq).</li><li>Familiarity with design patterns (e.g., Repository, Factory, Strategy).</li><li>Experience with SQL DBs, MySQL, Postgres, or MS SQL: writing queries, stored procedures, and performancetuning.</li><li>Knowledge of RESTful APIs and message-based systems.</li><li>Experience with relational databases and data access libraries (e.g., Entity Framework, Dapper).</li><li>Knowledge of ReactJS</li><li>Proficient in Git: branching, merging, pull requests, and version control workflows.</li></ul>

Responsibilities: <ul><li>Manage AR related activities in SAP including Customer Onboarding (as per policy), customer master database management, Credit Limit mapping, Pricing database update, Sales order release</li><li>Manage AR overdue status, claims processing, collection status, provisioning of doubtful debts, bad debts</li><li>Managing regularly AR balances reconciliations and liaison with commercial team and customers, consultants etc.</li><li>Support at month end for accruals, movements, documentation etc.</li><li>Support in statutory and internal audits related to above areas</li></ul> Requirements: <ul><li>Minimum 3 Years experience of SAP S4 for Sales / AR related Module</li><li>Minimum 3 Years experience of Alco Bev Industry – AR Management standpoint</li><li>Strong analytical skills with the ability to interpret data and drive business decisions.</li><li>Advanced proficiency in Excel and data analytics for reporting, forecasting, and planning.</li><li>Process-driven mindset, ensuring structured execution and business predictability.</li></ul>

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29 economic modeling Jobs found

Consultant, Data Analytics & Reporting-Food

Staff Electrical Engineer (Global Facilities Engineering)

Staff Engineer, Electrical – Global Facilities Engineering

Forward Deployed AI Strategist

Sales Operation Analyst

Commercial Finance Manager

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Manager, Data Engineering

Accounts Receivable (6 Months Contract)

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29 economic modeling Jobs found

Consultant, Data Analytics & Reporting-Food

Staff Electrical Engineer (Global Facilities Engineering)

Staff Engineer, Electrical – Global Facilities Engineering

Forward Deployed AI Strategist

Sales Operation Analyst

Commercial Finance Manager

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Manager, Data Engineering

Accounts Receivable (6 Months Contract)

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

EMPLOYER

TALENT

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Contact Us

JOBS BY SKILLS

JOBS BY FUNCTION

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WhiteCrow
WhiteCrow is on a mission to connect companies with the best talent across the globe.