Data & ML Architect

AVP, Digital Analytics

Business Intelligence Analyst

AVP – Model Ops Engineer

Data Analyst Manager

Financial Analyst

Manager, Data Science (GNS)

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</li></ul>

Responsibilities: <ul><li>Lead and deliver Digital Measurement Analytics for Digital Platforms in Agile methodology to drive digital data strategy that includes collection &amp; validation of data and reporting.</li><li>Partner with onsite Stakeholders and various process owners in marketing, technology and digital teams to plan and implement strategic priorities.</li><li>Present analytical results and actionable recommendations to key stakeholders on a recurring cadence, and propose innovative analytics solutions to drive business growth and enhance the customer experience.</li><li>Responsible for team’s effective communication, project deliverables, coaching team on adhering to expected timelines, accuracy &amp; compliance with meticulous project management.</li><li>Lead internal initiatives, perform other duties and/or special projects, as assigned.</li></ul> Requirements: <ul><li>Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 4+ years of hands-on relevant Analytics experience.</li><li>Minimum 6+ years of relevant work experience in lieu of specified degree.</li><li>2+ years of experience in Digital or Web Analytics Domain utilizing tools such as Adobe or Google Analytics and 2+ years of experience in SAS or SQL.</li><li>1+ years of Experience in Managing People, Coordinating work, Supervising, Evaluating performance and ensuring employees are trained.</li><li>Minimum 1+ years of experience in Data visualizations tools such as Tableau to drive insights.</li><li>Excellent oral and written communication skills with ability to collaborate, articulate and present solutions cutting across functional/agile teams in a simple yet compelling manner</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain dashboards and reports using Power BI and or Tableau</li><li>Connect to data sources including data warehouses (for example Redshift), ERP systems, and structured datasets</li><li>Prepare and transform data using Power Query, Tableau Prep, or similar tools</li><li>Build and maintain data models and calculations within BI tools to support scalable reporting</li><li>Translate business requirements into clear and effective visualizations and reports</li><li>Analyze data to identify trends, performance gaps, and opportunities for improvement</li><li>Ensure data accuracy by validating outputs against source systems and established definitions</li><li>Support user acceptance testing and incorporate feedback into reporting solutions</li><li>Maintain and enhance existing dashboards to improve usability and performance</li><li>Document key metrics, business logic, and report structures</li><li>Collaborate with cross-functional teams including business stakeholders and technical partners</li></ul> Requirements: <ul><li>Bachelor’s degree in Industrial engineering, Information Technology, Data Analytics, or related field</li><li>3 to 5 years of experience in Business Intelligence, Data Analytics, or Reporting roles</li><li>Experience developing dashboards using Power BI or Tableau</li><li>Experience working with enterprise data sources such as ERP systems or data warehouses</li><li>Experience supporting business or operational analytics, with supply chain exposure considered an advantage</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 5+ years’ experience or in lieu of degree, and 7+ years of relevant work experience in, data engineering or related roles in the financial services or regulated analytics domain.</li><li>Strong proficiency with data engineering tools and frameworks (e.g., Apache Spark, Airflow, Kafka, dbt, PySpark).</li><li>Proficient in programming languages such as SAS, Python, and SQL for building monitoring pipelines and validation checks.</li><li>Experience with cloud-based data infrastructure (e.g., AWS, Azure, GCP) and data warehousing (e.g., Snowflake, Redshift, BigQuery).</li><li>Familiarity with MLOps practices, model metadata tracking (e.g., MLflow), and monitoring toolkits (e.g., Evidently AI, Why Labs, Prometheus).</li><li>Understanding of model risk governance requirements and the role of data engineering in ensuring compliant model monitoring.</li><li>Ability to work in an agile environment and deliver high-quality, production-grade code in collaboration with DevOps and platform engineering teams.</li></ul>

Responsibilities: Core Analytics &amp; Insight Generation: <ul><li>Lead advanced analysis across digital behavior, customer engagement, campaign performance, funnel conversion, and eCommerce/POS sales impact.</li><li>Transform complex datasets into clear insights and recommendations that improve marketing performance, segmentation, and content targeting.</li><li>Conduct market, customer, and competitive analytics to identify opportunities, threats, and whitespace for growth.</li><li>Develop and maintain data-driven customer segments, ICP models, behavioral profiles, and opportunity sizing frameworks.</li></ul> Data Products, Measurement &amp; Reporting: <ul><li>Own and continuously optimize dashboards, analytical models, and reporting tools that enable visibility into performance and ROI.</li><li>Define and implement measurement frameworks, attribution logic, KPI hierarchies, and performance scorecards across marketing channels.</li><li>Build scalable data products that improve the accuracy, availability, and usability of marketing and commercial datasets.</li></ul> Data Management &amp; Governance: <ul><li>Ensure data quality, consistency, and governance across marketing, CRM, web analytics, and eCommerce datasets.</li><li>Partner with BI, Digital Technology, and data engineering teams to optimize data pipelines, tagging/instrumentation, and data taxonomy.</li></ul> Cross-Functional Analytics Partnership: <ul><li>Collaborate with marketing, sales, eCommerce, and product teams to understand business questions and translate them into analytical solutions.</li><li>Present insights to stakeholders at various levels, guiding decision‑making with clear narratives and fact‑based recommendations.</li><li>Share analytics best practices and educate teams on interpreting data and leveraging insights for better outcomes.</li></ul> Requirements: Desired Skills &amp; Experience: <ul><li>Strong quantitative and analytical skills with experience in digital analytics, customer analysis, attribution, and commercial data.</li><li>Ability to translate data into strategic insights and communicate them clearly to both technical and non‑technical stakeholders.</li><li>Experience with web analytics tools (e.g., GA4, Adobe), BI platforms (Power BI/Tableau), and CRM/marketing automation systems.</li><li>Technical proficiency in SQL, data modeling, and large dataset manipulation (preferred).</li><li>Detail-oriented with a strong sense of ownership, accountability, and proactive problem solving.</li><li>Demonstrated ability to partner cross‑functionally and influence decision‑making through data.</li><li>Comfortable working in a dynamic environment with evolving priorities.</li></ul> Required Qualifications: <ul><li>12 years+ experience overall, with 6+ years of experience in analytics, data insights, digital analytics, marketing science, business intelligence, or related fields.</li><li>Analytics function leadership &amp; team management experience preferred.</li><li>Strong experience analyzing digital marketing data, customer behavior data, funnel metrics, and/or commercial revenue datasets.</li><li>Experience in B2B, digital marketing analytics, or eCommerce analytics is highly valuable but not required.</li><li>Proven ability to turn complex datasets into business-ready insights and clear narratives.</li><li>Hands-on expertise with:</li><li>Web analytics platforms (GA4, Adobe Analytics)</li><li>BI tools (Power BI, Tableau)</li><li>CRM and marketing automation systems (Salesforce, Marketo, Eloqua, etc.)</li><li>Comfortable working with large &amp; complex datasets.</li><li>Demonstrated experience influencing decision‑making in a cross-functional environment.</li><li>Detail-oriented, accountable, and proactive in identifying and addressing analytical needs.</li></ul>

Responsibilities: Responsible for ensuring timely and quality financial planning and reporting, including: <ul><li>IT Cost Reporting</li><li>Departmental Spending</li><li>IPRB / Rationalisation / Cost Saving</li><li>Financial Review package Scrap</li><li>Spending analysis for Actual vs Outlook vs Budget for various areas such as: Operations, Factory support, R&amp;D, S&amp;M, G&amp;A expenses, etc and identify opportunities for cost improvement.</li><li>Analyze financial results and highlight key trends, variances, and risks.</li><li>Provide insights into revenue, expenses, and profitability performance</li><li>Prepare Quarterly Outlook / Yearly Budget for:</li><li>Operations, Factory support, R&amp;D, S&amp;M, G&amp;A expenses forecast)IT spending</li><li>IPRB / Rationalisation / Cost Saving Scrap</li><li>Ad hoc projects - Process Automation / Improvement</li></ul> Requirements: <ul><li>Degree in Engineering / Accountancy/ Business Admin</li><li>2 to 3 years of Finance, Accounting, or related work experience.</li><li>Proficient in Microsoft office skill, preferably knowledge of SAP</li><li>Knowledge of VBA Excel Programming and Tableau application will be an added advantage.</li><li>Able to work under Stressful environment &amp; tight deadline</li><li>Good in planning and organizational and analytical skill</li><li>Proactive and good problem-solving skills</li><li>Possess good interpersonal and communication skills</li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions.</li><li>Lead the development of AI and machine learning models to solve business problems.</li><li>Research, build, and deploy models based on shallow and deep machine learning.</li><li>Train robust NLP-based models on large datasets.</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs.</li><li>Design APIs for disseminating data science outputs.</li><li>Oversee the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions.</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high-bar for model development.</li></ul> Requirements: <ul><li>Have substantial experience in a senior data scientist role.</li><li>Have experience in leading complex projects and customer relationships.</li><li>Have significant experience in managing larger Technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li></ul> Highly Desired Skills and Experience: <ul><li>PhD or Masters degree in Computer Science, Mathematics, Statistics, or a related field.</li><li>7-10+ years of experience in AI and machine learning.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

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Data & ML Architect

AVP, Digital Analytics

Business Intelligence Analyst

AVP – Model Ops Engineer

Data Analyst Manager

Financial Analyst

Manager, Data Science (GNS)

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Data & ML Architect

AVP, Digital Analytics

Business Intelligence Analyst

AVP – Model Ops Engineer

Data Analyst Manager

Financial Analyst

Manager, Data Science (GNS)

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

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