Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Commercial Planning Analyst

Senior AI Engineer

Manager II – Quality & Reliability Engineer

Supervisor – Quality and Reliability Engineer

Senior Site Quality Manager

Manager II – Quality & Reliability Engineering

Business Intelligence Developer

Analytics Lead/Lead Data Integration Engineer

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Dashboard Design and Development: Design, develop, and maintain interactive and user-friendly dashboards in PowerBI and Looker, focusing on clarity, performance, and data accuracy.&nbsp;</li><li>Data Lake Integration: Connect to and leverage data from various data lake sources on GCP, ensuring seamless data flow for visualization purposes.&nbsp;</li><li>Semantic Model Development: Develop and maintain robust semantic models in Looker (LookML) and PowerBI, ensuring data consistency, accuracy, and ease of use for reporting and analysis. This includes defining dimensions, measures, relationships, and calculations.&nbsp;</li><li>Machine Learning and GenAI Visualization: Create compelling visualizations to effectively communicate the results, performance, and insights derived from machine learning models and GenAI applications. This may involve visualizing model predictions, feature importance, natural language processing outputs, and other relevant data.&nbsp;</li><li>GCP Expertise: Utilize your strong understanding of GCP services to access, process, and prepare data for visualization. This may involve working with services such as BigQuery, Cloud Storage, and potentially data engineering pipelines built on GCP.&nbsp;</li><li>Collaboration: Partner closely with data scientists, data engineers, product managers, and business stakeholders to understand their data visualization needs and translate them into effective visual solutions.&nbsp;</li><li>Requirements Gathering: Elicit and document visualization requirements from various stakeholders, ensuring alignment with business objectives.&nbsp;</li><li>Performance Optimization: Optimize dashboard and visualization performance to ensure fast load times and efficient data rendering.&nbsp;</li><li>Data Quality Assurance: Ensure the accuracy, consistency, and reliability of data presented in visualizations.&nbsp;</li><li>Best Practices and Standards: Establish and enforce data visualization best practices and standards across the organization.&nbsp;</li><li>Training and Support: Provide guidance and support to other team members on data visualization tools and techniques.&nbsp;</li><li>Continuous Learning: Stay up to date with the latest trends and advancements in data visualization, PowerBI, Looker, GCP, and related technologies, particularly in the context of AI/ML.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s or master’s degree in computer science, Data Science, Statistics, Information Systems, or a related field.&nbsp;</li><li>Minimum of 3 years of experience as a Visualization Expert, Data Visualization Engineer, or a similar role.&nbsp;</li><li>Proven expertise in designing and developing interactive dashboards and reports using PowerBI and Looker.&nbsp;</li><li>Strong experience in connecting to and working with data lakes, preferably on the Google Cloud Platform (GCP).&nbsp;</li><li>Solid understanding and hands-on experience in developing semantic models, particularly with LookML in Looker and data modeling within PowerBI.&nbsp;</li><li>Preferable experience in creating visualizations specifically for machine learning and GenAI applications, understanding the nuances of presenting model outputs and insights.&nbsp;</li><li>Proficiency in SQL for data extraction and manipulation.&nbsp;</li><li>Familiarity with data warehousing concepts and data modeling techniques.&nbsp;</li><li>Experience with data preparation, ELT (preferred) / ETL processes.&nbsp;</li><li>Strong analytical and problem-solving skills with the ability to interpret complex data.&nbsp;</li><li>Excellent communication and presentation skills, with the ability to convey technical information to both technical and non-technical audiences.&nbsp;&nbsp;</li><li>Ability to work independently and collaboratively in a fast-paced environment.&nbsp;&nbsp;</li><li>Strong portfolio showcasing your data visualization skills and experience.&nbsp;</li></ul>

Responsibilities: <ul><li>Work together with Sales / Commercial team also external key distributors to consolidate sales data from different countries / market, ensuring the data accuracy, cleanliness, and integrity.</li><li>Lead the maintenance and enhancement of commercial reporting processes, including the preparation of monthly reports and the development of automated reporting solutions and dashboards.</li><li>Provide sales team with commercial analysis and reporting to support team objectives and decision-making processes.</li><li>Initiate and standardize templates (Excel and PowerPoint) for projects as required</li><li>Formulate and execute new commercial KPI tracking mechanisms to support performance evaluation.</li><li>Participate in sales / commercial pertinent projects / Global project (ie. Game Plan / Distributor Excellence Program) and collaborate cross-functionally to ensure successful implementation and alignment with organizational objectives.</li><li>Work together with Sales / Commercial team to drive the commercial plans (Calendar of Activities).</li><li>Help to manage our JBP (Joint Business Plan) and contracts through data availability</li></ul> Requirements: <ul><li>Bachelors degree in related field</li><li>Minimum 2 years working at medium to large FMCG company</li><li>Advanced Microsoft Office Excel (Commercial Dashboard, XLookup, IF conditional, Data consolidation, Data cleaning, Conditional formatting) and Power Point</li><li>Good command in English</li><li>Takes ownership, self-determination, always looking to improve, collaborative approach on cross-functional working</li></ul>

Responsibilities: <ul><li>Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.</li><li>Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support</li><li>Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.</li><li>Build innovative AI solutions tailored to business requirements.</li><li>Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.</li><li>Communicate complex technical concepts and results to non-technical audiences effectively.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools</li><li>Lead the design and development of solutions using Agentic AI</li></ul> Requirements: Basic Qualifications: <ul><li>Bachelor’s or Master’s in Computer Science, Mathematics, Statistics, or a related field.</li><li>8+ years of experience in software engineering, data science, AI, or a related field.</li><li>Proficiency in software development and statistical analysis.</li><li>Experience with Large Language Models and their applications.</li><li>Strong communication skills and the ability to present technical results to business stakeholders.</li><li>Experience with solution architecting and design.</li><li>Hands-on experience with cloud platforms such as Azure and/or AWS.</li><li>Proficiency in programming languages such as Python, R, or similar.</li><li>Strong problem-solving skills and the ability to work independently as well as part of a team.</li></ul> Preferred Qualifications: <ul><li>Experience with large language models and supporting workflows.</li><li>History of project leadership and development.</li><li>Familiarity with Agile development.</li><li>Experience in applications on sales, marketing, and market research.</li><li>Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.</li><li>Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support.</li><li>Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.</li><li>Build innovative AI solutions tailored to business requirements.</li><li>Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.</li><li>Communicate complex technical concepts and results to non-technical audiences effectively.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools.</li><li>Lead the design and development of solutions using Agentic AI.</li></ul>

Responsibilities: 1. Team Leadership <ul><li>Manage, mentor, and develop a team of Quality and Reliability Engineers.</li><li>Assign projects and tasks based on individual strengths and organizational priorities.</li><li>Conduct performance evaluations and provide coaching for continuous improvement.</li><li>Lead cross-functional problem-solving teams to address customer quality issues, reduce DPPM, and lower the cost of poor quality.</li></ul> 2. Quality Assurance <ul><li>Develop and implement robust quality control processes and procedures.</li><li>Oversee customer quality audits and ensure compliance with our client quality policies and customer requirements.</li><li>Analyze quality data and metrics to identify trends and areas for improvement.</li></ul> 3. Failure Analysis <ul><li>Lead structured failure investigations (e.g., fault tree analysis) to determine root causes and corrective actions.</li><li>Coordinate product testing related to customer-reported issues.</li><li>Serve as the primary quality interface with customers on escalations, reliability matters, and compliance.</li></ul> 4. Project Management <ul><li>Lead quality and reliability improvement projects from concept through completion.</li><li>Collaborate cross-functionally with Sales, Engineering, and Operations to align on customer quality objectives.</li><li>Support supplier reviews, customer audits, and on-site technical support.</li><li>Conduct periodic business reviews with key customers on DDN quality and reliability performance.</li></ul> 5. Continuous Improvement <ul><li>Identify opportunities for process optimization, cost reduction, and improved efficiency.</li><li>Implement Lean and Six Sigma methodologies to drive continuous improvement.</li><li>Collaborate with Engineering and Sales to share the DDN strategic quality roadmap and strengthen customer partnerships.</li></ul> 6. Reporting and Communication <ul><li>Prepare and present reports on quality and reliability metrics to senior leadership.</li><li>Communicate effectively with internal and external stakeholders on quality matters and escalations.</li><li>Provide Voice of the Customer (VoC) feedback to Product Management, Engineering, and Manufacturing to mitigate risks.</li></ul> 7. Tactical Initiatives <ul><li>Proactively identify and remove roadblocks affecting quality and customer satisfaction.</li><li>Drive urgency and accountability across teams to meet customer expectations.</li><li>Bridge communication between customers and internal teams to ensure timely problem resolution.</li></ul> Requirements: Qualifications and Experience <ul><li>Education: Bachelor’s degree in Electrical, Mechanical, or related Engineering field; Master’s degree preferred.</li><li>Experience: Minimum 7 years in Quality Assurance or Reliability Engineering, including at least 3 years in a managerial or global capacity.</li></ul> Technical Skills: <ul><li>Strong knowledge of Quality Management Systems (QMS), Statistical Process Control (SPC), Gage R&amp;R, and reliability tools.</li><li>Experience with failure analysis using structured methodologies (e.g., fault tree analysis).</li></ul> Certifications: <ul><li>Six Sigma Black Belt, ASQ Certified Quality Engineer (CQE), or equivalent preferred.</li></ul> Soft Skills: <ul><li class="ql-indent-1">Strong leadership and team development skills.</li><li class="ql-indent-1">Excellent problem-solving, communication, and interpersonal abilities.</li><li class="ql-indent-1">Demonstrated customer interface experience in data center interconnect technology.</li><li class="ql-indent-1">Executive-level presence with the ability to influence across all levels of the organization.</li></ul>

Responsibilities: <ul><li>Manage the day-to-day activities of the team in a safe environment and be responsible for Health and Safety goals.</li><li>Deliver on all KPIs that help the business achieve its objectives.</li><li>Lead and drive QA initiatives within the functional area.</li><li>Provide quality input and support to Manufacturing, Engineering, Prototype, and Commercial functions.</li><li>Lead, coordinate, and maintain risk assessment documentation (e.g., FMEAs).</li><li>Investigate the root cause of quality issues and implement timely and effective corrective actions to prevent recurrence for both customer and internal issues.</li><li>Strategically lead new product introduction (NPI) and contract reviews from a QA perspective.</li><li>Prepare and update Operations procedures and associated documentation.</li><li>Overall responsibility for functional area GMP standards and compliance, including promoting quality awareness.</li><li>Establish inspection standards, sampling plans, and test methods.</li><li>Report quality metrics to management.</li><li>Develop strong links with customer organizations and other project stakeholders.</li><li>Review validation documentation for the functional area.</li><li>Perform and support internal and external audits to ISO and FDA requirements.</li><li>Actively contribute to the continuous improvement of the Quality Management System.</li><li>Supervise and provide direction to quality personnel.</li><li>Perform other tasks as directed by the Operations Quality Manager in line with company goals.</li></ul> Requirements: <ul><li>Level 8 degree in Science, Engineering, or related field.</li><li>Minimum of 5 years industry experience in a medical device manufacturing environment.</li><li>People management experience.</li></ul> Key Requirements <ul><li>Clear understanding of medical device quality systems and requirements, including measurement techniques.</li><li>Experience managing and leading a team.</li><li>Strong CAPA experience.</li><li>Strong root cause analysis and problem-solving skills.</li><li>Knowledge of FDA and ISO Quality systems for medical device companies is desirable.</li><li>Experience in new product introduction (NPI) and manufacturing process transfers is desirable.</li><li>Demonstrated excellent organizational skills and ability to work independently.</li><li>Excellent written and verbal communication skills.</li></ul>

Responsibilities: <ul><li>Lead and develop the quality team, fostering a culture of continuous improvement and cross-department collaboration.</li><li>Partner with manufacturing, engineering, and global quality teams to ensure product quality, process capability, and regulatory compliance.</li><li>Champion and uphold plant-wide quality standards, policies, and systems in alignment with corporate and customer requirements.</li><li>Monitor and report key quality performance indicators (e.g., customer complaints, internal defects) and provide actionable insights to plant leadership.</li><li>Manage internal and external audits and ensure audit readiness across the facility.</li><li>Oversee plant-wide quality improvement initiatives to reduce defects and scrap and improve process control and product reliability.</li><li>Lead root cause analysis, corrective actions, and continuous improvement efforts to address recurring quality issues.</li><li>Collaborate with engineering and production teams to ensure new product introduction (NPI) meets quality standards.</li><li>Mentor and coach quality team members to foster a high-performance culture.</li><li>Travel as required to support internal and external customer needs and NPI programs.</li></ul> Requirements: <ul><li>Bachelor’s degree in Engineering, Quality, or a related technical field (preferred).</li><li>8+ years of progressive quality experience in a manufacturing environment.</li><li>Strong knowledge of ISO 9001 and regulatory compliance standards.</li><li>Minimum of 3 years in a leadership role managing quality teams.</li><li>Expertise in Lean Manufacturing and advanced quality methodologies.</li><li>Proven experience with 8D problem solving, FMEA, DOE, SPC, and safe launch processes.</li><li>Proficiency in quality data analysis tools such as Minitab, JMP, or similar.</li><li>Excellent communication, analytical, and leadership skills, with the ability to inspire and motivate teams.</li></ul>

Responsibilities: <ul><li>Lead development and execution of standardized DfRE and RV methodologies across Converged Products.</li><li>Champion a Design for Six Sigma (DFSS) culture, mentoring and training product design teams.</li><li>Oversee product validation, including HALT/HAST testing, Test-to-Failure (TTF) methodologies, and DOE approaches.</li><li>Collaborate with Product Development Engineering (PDE), Manufacturing Process Development Engineering (MPDE), Field Application Engineering (FAE), and Advanced Quality Engineering (AQE) teams to integrate reliability considerations throughout the product lifecycle.</li><li>Develop comprehensive test and validation plans aligned with our client LeanPD stage-gate approach.</li><li>Drive early concept testing, failure mode identification, and iterative product design improvements.</li><li>Support failure analysis (F/A), Root Cause and Corrective Action (RCCA), and competitive benchmarking activities.</li><li>Partner with Global R&amp;T COE to develop custom test equipment, test systems, and software for unique testing requirements.</li><li>Manage and coach a high-performing team, ensuring clear accountability, skill development, and work-life balance.</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Electrical Engineering, Electronics, or Mechatronics.</li><li>10+ years of experience in all aspects of reliability engineering for electronic or mechatronic products (reliability estimation, calculation, and risk identification).</li><li>Extensive experience with test equipment, test systems, labs, HALT/HAST testing, validation plans, and custom test systems.</li><li>Proven experience working with global, cross-functional engineering teams in multi-site organizations.</li><li>Strong analytical, critical thinking, and problem-solving skills.</li><li>Knowledge of FIT estimation methodology, Weibull/Chi-Square statistical analysis, FMEDA, FTA, and Bayes theorem applications.</li><li>Reliability engineering training from ASQ, TUV, Reliasoft, or equivalent.</li><li>Excellent written and verbal communication skills in English.</li><li>Willingness to travel up to ~20%.</li></ul>

Responsibilities: <ul><li>Client is seeking a skilled Business Intelligence Developer to design, build, and maintain enterprise-scale data products and data sources using platforms like Tableau and Streamlit.</li><li>The ideal candidate will be a detail-oriented developer with strong technical skills who can translate business requirements into robust analytical solutions.</li><li>This role requires a mixture of business acumen and technical expertise, along with an ability to build strong partnerships and collaborate to solve problems.</li><li>Design, develop, and maintain interactive data products and reports in Tableau, Streamlit, and other BI tools.</li><li>Build and optimize data sources, ensuring data integrity and performance at enterprise scale</li><li>Collaborate with business stakeholders to gather requirements and translate them into technical specifications.</li><li>Develop scalable data product solutions that can accommodate growing user bases and data volumes.</li><li>Implement best practices for data product design, data modeling, and visualization techniques.</li><li>Monitor data product performance and user adoption, making improvements as needed.</li><li>Maintain documentation for data products, data sources, and development processes.</li><li>Troubleshoot and resolve technical issues with existing data products and data connections.</li><li>Support data governance initiatives by ensuring consistent data definitions and calculations across reports.</li><li>Participate in code reviews and maintain version control for BI development projects.</li><li>Stay current with BI tool updates and emerging visualization technologies.</li><li>Provide technical support to end users and assist with data product-related questions.</li><li>Contribute to the development of reusable components and templates for efficiency gains.</li></ul> Requirements: Qualifications <ul><li>3+ years in the data space as an analyst, engineer, or equivalent.</li><li>3+ years experience designing, implementing, operating, and extending enterprise dimensional models.</li><li>3+ years working with a large-scale data warehouse, preferably in a cloud environment.</li><li>3+ years of hands-on experience developing data products and reports in Tableau, including advanced calculations, parameters, and complex visualizations.</li><li>Experience with Streamlit or similar Python-based data product frameworks.</li><li>Experience with modern data stack technologies including cloud data warehouses (AWS/Snowflake) and ELT tools.</li><li>1+ years maintaining a project workstream to identify tasks, milestones, and deliverables.</li><li>Bachelors degree in Computer Science, Information Systems, Mathematics,</li></ul>

Responsibilities: <ul><li>Act as a technical guide on one or more applications utilized by company.</li><li>Work with the Business System Analyst to ensure designs satisfy functional requirements.</li><li>Work with large, complex data sets and high throughput data pipelines that meet business requirements.</li><li>Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.</li><li>Build data and analytics tools that utilize the data pipeline to provide actionable insights to operational efficiency and other key business&nbsp;</li><li>performance metrics.</li><li>Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs.</li><li>Collaborate with data scientists and architects on several projects.</li><li>Solve various complex problems</li></ul> Requirements: <ul><li>Minimum of 6 years of related experience</li><li>Bachelors degree preferred or equivalent experience</li></ul>

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43 statistical modeling Jobs found

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Commercial Planning Analyst

Senior AI Engineer

Manager II – Quality & Reliability Engineer

Supervisor – Quality and Reliability Engineer

Senior Site Quality Manager

Manager II – Quality & Reliability Engineering

Business Intelligence Developer

Analytics Lead/Lead Data Integration Engineer

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43 statistical modeling Jobs found

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Commercial Planning Analyst

Senior AI Engineer

Manager II – Quality & Reliability Engineer

Supervisor – Quality and Reliability Engineer

Senior Site Quality Manager

Manager II – Quality & Reliability Engineering

Business Intelligence Developer

Analytics Lead/Lead Data Integration Engineer

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

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