Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Actuarial Consultant

Manager, Data Engineering

Senior Manager - Portfolio Development

Accounts Receivable (6 Months Contract)

Product Engineer II

Finance Analyst

Senior Data Engineer

AVP – Evergreen Data Product Owner

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>Readiness to the role as per the Retirement career path / skill blocks</li><li>Demonstrate a positive attitude in dealing with changes, reacting to them in a calm, professional manner and actively seeking solutions to any problems which might arise as a result of the changes.</li><li>Adopt a business-friendly writing style when communicating with UK colleagues and drafting advice for clients.</li><li>The content will be focused and concise, with significant actions, information, deadlines and recommendations clearly identified. Avoid using unnecessary colloquialisms, formalities and jargon.</li><li>Prepares original materials (letters, reports, discussion guides) for the lead actuary including first draft of commentary on results</li><li>Fully understands UK pensions legislation, work as an expert scrutiniser on all major work types – Actuarial Valuation / Accounting / Consulting support services / GMP equalisation</li><li>Ability to stand back from detailed calculations, sense-check, draw conclusions and see the work in a broader context of the clients needs and the legislative framework.</li><li>Answers client questions without reliance on the lead actuary and is a strong backup to lead actuary</li><li>Ensures own work and work of junior colleagues is complete and thorough, requiring minimal review from lead actuary</li><li>Identifies and implements improvements to the various processes</li><li>Champions of new ideas and initiatives that deliver strategic results</li><li>Plan and execute technical meetings and training as per the teams requirement for the Individual contributor roles</li><li>Create an open, collaborative, and engaging team environment&nbsp;</li></ul> Requirements: <ul><li>Strong analytical and mathematical skills, with a keen eye for detail</li><li>Ability to effectively communicate the team goals and drive business results</li><li>Understands the professional requirements and quality standards for UK work</li><li>Strong organizational skills to manage multiple projects and deadlines efficiently</li><li>Ability to work in a team and collaborate effectively with colleagues from diverse backgrounds</li><li>An expert in one or more of the specialist areas – valuation, accounting, client extension work, risk &amp; modelling, GMP equalisation, cash equivalent transfer value – but will have a general understanding of all the work and the ability to adapt to new work.&nbsp;</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>

Key Responsibilities: Global Portfolio Strategy <ul><li>Define and implement a unified global portfolio vision to meet future consumer/customer needs for filters and beyond filters (combustibles and next generation products)</li><li>Direct multi category program and project management to ensure innovation efforts are focused towards building a healthy portfolio</li><li>Balance global consistency with regional customization to maximize market relevance and profitability.</li><li>Oversee portfolio lifecycle management, including launches, rationalization, and category transitions.</li></ul>&nbsp;Market &amp; Consumer Insights <ul><li>Lead global research initiatives to capture consumer trends, competitive intelligence, and regulatory shifts across regions.</li><li>Translate insights into global portfolio strategies and innovation pipelines</li></ul> Innovation &amp; Product Development <ul><li>Drive global innovation programs, ensuring new products meet consumer demand and comply with international regulations.</li><li>Be the one stop shop for innovation – where commercial team and customers channel their initial ideas and requests before being formalized into innovation projects</li></ul>&nbsp;Cross-Regional Leadership <ul><li>Align regional commercial directors and managers under a global framework.</li><li>Facilitate knowledge sharing and best practices across markets to accelerate growth.</li><li>Act as the key liaison between commercial, operations and innovations teams</li></ul>&nbsp;Regulatory &amp; Compliance Oversight <ul><li>Monitor and interpret global regulatory developments impacting tobacco categories.</li><li>Ensure portfolio decisions adhere to international laws, trade agreements, and corporate responsibility standards.</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s degree in engineering ,Business, Marketing, Economics, or related field; MBA strongly preferred.</li><li>12+ years of experience in FMCG, tobacco, or regulated industries, with at least 5 years in global portfolio/category leadership.</li><li>Deep understanding of international tobacco industry dynamics, consumer behavior, and regulatory frameworks.</li><li>Proven track record in global strategic planning, innovation, and cross-market leadership.</li><li>Exceptional communication, negotiation, and stakeholder management skills across diverse cultures.</li></ul>&nbsp;Competencies <ul><li>Strategic global mindset with commercial acumen.</li><li>Ability to balance global consistency with local market needs.</li><li>Leadership and team development across geographies.</li><li>Strong influencing skills in complex stakeholder environments.</li><li>Ethical decision-making and commitment to responsible global business practices.</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>

Responsibilities: Performance &amp; Continuous Improvement: <ul><li>Maintain and improve existing products, processes, and specifications</li><li>Drive quality improvements and cost reduction initiatives</li><li>Support product extensions to meet specific customer requirements</li></ul> Daily &amp; Ongoing Activities: <ul><li>Manage engineering change processes (ECR/ECN)</li><li>Lead Product Change Notifications (PCN) to customers</li><li>Conduct root cause analysis and implement corrective actions</li><li>Redesign products to resolve customer complaints and manufacturing challenges</li><li>Coordinate with cross-functional teams for seamless implementation</li></ul> Periodic Responsibilities; <ul><li>Support supplier development and consolidation initiatives</li><li>Participate in A3 problem-solving, Material Review Board, and Rapid Response Board</li><li>Assist manufacturing facilities with processing issues</li><li>Collaborate with product management, sales, and customer service teams</li><li>Develop and execute product testing plans</li><li>Ensure compliance with military specifications (MIL-STD)</li></ul>&nbsp;Requirements: Education <ul><li>Bachelor’s Degree in Mechanical Engineering, Mechatronics Engineering, or equivalent</li></ul> Experience &amp; Skills <ul><li>2–3 years in product engineering or packaging engineering</li></ul> Strong expertise in: <ul><li>3D Modeling (CREO / SolidWorks / Pro-E)</li><li>GD&amp;T (Geometric Dimensioning &amp; Tolerancing)</li><li>Engineering Change Management (ECR/ECN/PCN)</li><li>Lean Manufacturing &amp; Continuous Improvement</li><li>Root Cause Analysis (A3 / 8D methodologies)</li><li>Supplier Development</li><li>Microsoft Office tools</li><li>Knowledge of military specifications (MIL-STD) is a strong advantage&nbsp;</li></ul>

Responsibilities: <ul><li>Ensure timely and high-quality financial planning and costing activities, which include preparing the Monthly Financial Review package, executing Monthly Cost Rollup and Product Cost/AUC simulations, and setting standard rates on a half-yearly basis.</li><li>Conduct variance analysis comparing Actual vs Outlook vs Budget for areas such as Output Quantity, Standard Cost Absorption, Material Consumption, Inventory Changes, and Utilization.</li><li>Prepare Quarterly Outlooks and Yearly Budgets, including coordination for Internal Sales and Purchases with inter-company counterparts.</li><li>Participate in ad hoc projects, such as process automation and improvement initiatives.</li></ul> Requirements: <ul><li>Educational Background: Applicants should possess a degree in Accountancy, Business Administration, or Economics.</li><li>Experience: Two to three years of experience in Financial Planning and Analysis, Accounting, Costing, or a related field is required.</li></ul>

Responsibilities: Data Infrastructure:&nbsp; <ul><li>Prepares data infrastructure to support the efficient storage and retrieval of data.</li></ul> Data Formats:&nbsp; <ul><li>Examines and resolves appropriate data formats to improve data usability and accessibility across the organization.</li></ul> Data &amp; Analytical Solutions:&nbsp;&nbsp; <ul><li>Develops complex data products and solutions using advanced engineering and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li></ul> Data Pipelines:&nbsp;&nbsp; <ul><li>Develops and maintains 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></ul> Data Systems:&nbsp;&nbsp; <ul><li>Reviews existing data systems and architectures to identify areas for improvement and optimization.</li></ul> Stakeholder Management: <ul><li>Collaborates with multi-functional data and advanced analytic teams as well as with business teams to gain requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li></ul> Data Frameworks:&nbsp; <ul><li>Builds complex prototypes to test new concepts and implements data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li></ul> Automated Deployment Pipelines:&nbsp;&nbsp; <ul><li>Develops automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li></ul> Data Modeling:&nbsp;&nbsp; <ul><li>Performs complex data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience.&nbsp;</li><li>Typically reflects 5 years or more of relevant experience.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust pipelines to collect, transform, and store data used in model monitoring workflows (e.g., scoring data, performance metrics, outcomes).</li><li>Build scalable data architectures to support real-time and batch monitoring, including data ingestion, enrichment, and retention practices.</li><li>Develop reusable monitoring components (e.g., performance drift detectors, threshold-based alerts, metric repositories) that support various model types and regulatory needs.</li><li>Integrate data pipelines with model lifecycle platforms, MLOps tools, and observability solutions to ensure seamless model performance tracking.</li><li>Partner with model risk and compliance teams to ensure data lineage, audit trails, and documentation are preserved and accessible for regulatory reviews (e.g., SR 11-7 compliance).</li><li>Collaborate with data scientists, model validators, and product managers to align monitoring data infrastructure with evolving model monitoring requirements.</li><li>Work closely with the model monitoring analytics and strategy monitoring analytics teams within MO&amp;A to ensure the monitoring data infrastructure adapts to changing analytics and monitoring needs. Enable visualization and reporting capabilities through dashboards (e.g., Power BI, Tableau) that summarize model health, stability, and issue alerts.</li><li>Designing and maintaining high-performance data pipelines that ingest, transform, and version datasets for Model and Strategy Monitoring</li><li>Optimize data storage and compute performance for large-scale monitoring use cases involving high-frequency scoring or model ensembles.</li></ul> Requirements: <ul><li>Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 7+ years’ experience OR, in lieu of degree, and 9+ years experience with program or product management experience leading complex, cross-functional data or analytics programs.</li><li>7+ years of of experience managing programs or products, including: 5+ years of experience defining business needs, prioritizing data and analytics solutions, and coordinating cross-functional technical execution and 3+ years of experience working in data integration, modeling, warehousing, or big data environments—preferably supporting modeling or advanced analytics.</li><li>Demonstrated experience leading Agile or Scaled Agile programs (SAFe) across cross-functional teams.</li><li>Proven track record of enabling model or analytics platforms, data-as-a-product delivery, or Model Lifecycle Operations/Data Operations functions.</li><li>Agile or Product Owner certification (e.g., CSPO, SAFe PO/PM).</li><li>Broad understanding of credit risk, fraud, marketing analytics, regulatory modeling (e.g., CECL, Basel), or consumer lending data environments.</li><li>Experience working with large-scale data ecosystems, including cloud (AWS, Azure), data lakes, and metadata management tools.</li></ul>

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46 economic modeling Jobs found

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Actuarial Consultant

Manager, Data Engineering

Senior Manager - Portfolio Development

Accounts Receivable (6 Months Contract)

Product Engineer II

Finance Analyst

Senior Data Engineer

AVP – Evergreen Data Product Owner

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46 economic modeling Jobs found

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Actuarial Consultant

Manager, Data Engineering

Senior Manager - Portfolio Development

Accounts Receivable (6 Months Contract)

Product Engineer II

Finance Analyst

Senior Data Engineer

AVP – Evergreen Data Product Owner

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

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