Senior Business Intelligence Analyst

Associate Data Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Director, Data Science

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist

Lead Software Engineer, QA

Java Backend Engineer

Android - Sr/Staff Software Engineer

Role Description: <ul><li>The Continuous Improvement EMIA team reports to Operations Automotive EMIA.</li><li>By providing new generation digital solutions to our Operational teams across EMIA, our team creates full transparency and speed in the ongoing digital &amp; lean transformation(s), which will enable all involved functions to leverage data to develop business insights and roadmap updates based upon clearly arranged and understandable data. Due to the extended scope, focusing also on the connecting processes from Supplier(s) to Manufacturing ending at the Customer(s) (internal and external) we will function as ‘the’ differentiator for our Company.</li><li>The Data Scientist Automotive EMIA will report to the Smart Factory Leader Automotive EMIA.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Lead projects and work together with our Automotive EMIA Operations plants, internal (IT, , Corporate Technology, CoE, SC, ..) and external partners in the area of Smart Factory (Applications, ML, AI, DL), aligned with Operations Automotive EMIA Strategy.</li><li>Lead Smart Factory improvement projects (Enhancements) of existing applications together with internal / external supplier and customers (project management) until the level of RTD (Ready To Deploy)</li><li>·Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems.</li><li>Identify and interpret data sources, manage large amounts of data, merge data sources together, ensure consistency of datasets, create visualizations to aid in understanding data.</li><li>Develop, Validate and Deploy (including Training and Coaching of the users) until the level of RTD (Ready To Deploy), Digital Factory Applications, ML models, contributing to waste elimination and efficiency improvements within all Operations functions (Manufacturing, Quality, SC, LOG, ….), this together with our internal and external partners.</li></ul>&nbsp;Requirements: Desired candidate &amp; Qualification <ul><li>Good understanding of a technology driven manufacturing company.</li><li>Knowledge of the core manufacturing technologies: Stamping, Plating, Assembly, Molding.</li><li>Experienced with data visualization tools like PowerBi, Tableau, ThingWorx,..</li><li>Good applied statistics skills, such as distributions, statistical testing, regression, etc.</li><li>Development experience in programming languages R, Python.</li><li>Knowledge, experience in JAVA scripting</li><li>Excellent pattern recognition and predictive modelling skills.</li><li>Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, neural networks and deep learning etc.</li><li>Experience in technologies like, Jupyter Notebooks, Numpy, Pandas, Seaborn, Scikit-learn, PyTorch and TensorFlow.</li><li>Exposure to recent developments in Deep Learning, Gen AI, Agentic AI domain.</li><li>Database skills, on-premises and cloud based.</li><li>Experience in AWS is an advantage, functional knowledge of AWS platforms such as Sagemaker, S3, and RedShift.</li><li>Excellent presentation skills in both spoken en written English.</li><li>&nbsp;Excellent and strong communicator</li><li>The ability to translate, explain and bring, complex data science topics to an easy understandable level, speeding up acceptance level in general.</li><li>Bachelor or master’s in data science</li><li>Team player with a solution focused problem-solving mentality.</li><li>Change agent with high Execution level, including training and coaching talents.</li><li>Passioned about the combination of Technology, Data, Analytics and Statistics with link to Quality, Product and Process Engineering</li><li>Inspired by and searching actively for new technologies and methods.</li></ul>

Responsibilities: <ul><li>Ability to troubleshoot problems in a live environment and provide real time help with critical issues.</li><li>Write code that is easily understood and maintainable by other team members.</li><li>Keep up to date with developments in technologies we are using.</li><li>Ability to communicate and work effectively, supporting various business departments.</li><li>Ability to work in fast-paced interdisciplinary environment.</li></ul> Requirements <ul><li>BA/BS in Computer Science or equivalent practical experience.&nbsp;</li><li>At least 3+ years of post-university experience as a full-stack engineer.</li><li>Solid knowledge of programming fundamentals—algorithms, data structures, design patterns, and paradigms.</li><li>Strong knowledge of Python.</li><li>Solid knowledge SQL and relational databases.</li><li>Knowledge of Extract-Transform-Load (ETL) and big data analytics tools.</li><li>Experience working in a cloud environment (AWS, Azure, GCP).</li><li>Familiarity with popular Python data analytics frameworks.</li><li>Familiarity with Snowflake or other large analytics engines.</li><li>Experience with data warehousing and working in environments with large scale, complex analytics requirements.</li><li>Familiarity with DAG-based job scheduling tools.</li><li>Cloud-native container orchestration platforms and tools.</li><li>Experience working in the Financial Services industry.</li></ul>

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: Strategic Leadership:&nbsp; <ul><li>Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li></ul> Team Management:&nbsp; <ul><li>Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li></ul> Advanced Research Direction:&nbsp; <ul><li>Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li></ul> Machine Learning and AI Solutions:&nbsp; <ul><li>Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li></ul> Data Collection and Preparation:&nbsp; <ul><li>Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li></ul> Data Visualization Strategy:&nbsp; <ul><li>Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li></ul> Cross-functional Collaboration:&nbsp; <ul><li>Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li></ul> Model Deployment and MLOps:&nbsp; <ul><li>Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li></ul> Documentation Standards:&nbsp; <ul><li>Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li></ul> Budget and Resource Management:&nbsp; <ul><li>Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li></ul> Ethical AI Governance:&nbsp; <ul><li>Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</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></ul> Requirements: <ul><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>

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>

Responsibilities: <ul><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems. Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units. Overseeing 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>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units.</li><li>Overseeing the scaling of production systems to meet growing demands.</li></ul> Requirements: <ul><li>Possess an advanced or Masters education in Computer Science, Mathematics, Statistics, or a related field. Have experience working directly with large language models and transformer-based architectures including BERT, RoBERTa, T5 etc.</li><li>Be proficient in working with big data technologies and tools like Hadoop, Spark, or AWS.</li><li>Have experience and knowledge of applying LLMs including ChatGPT, GPT 3.5, Claude, Mistral, etc.</li><li>Be a natural problem solver, able to lead and mentor junior data scientists, and collaborate with cross-functional teams.</li><li>Demonstrate proficient experience with machine learning algorithms, including deep learning, gradient boosting, and random forests Possess advanced programming skills in Python, R, or other relevant languages for data analysis.</li></ul>

Role Description: <ul><li>Company’s Global R&amp;D team is looking for embedded software engineers and technical leaders to help build the future of industrial Automation &amp; Solutions.</li><li>You will have cross functional interactions and working closely with hardware, software, and product management teams.</li></ul> Responsibilities: As a Lead Software Engineer, the individual will work be in Embedded Software Development team. <ul><li>You provide the embedded platform infrastructure to enable our Industrial Networking Products.</li><li>You dedicate your creativity to a cross-functional, self-organized, agile team of developers.</li><li>You communicate with product owners, software architects and application developers in an intercultural and global work environment.</li><li>You contribute to the implementation of a Linux based Operating system for in-field embedded device families.</li><li>You assure the secure development life cycle of the platform and harden the attack surface of devices.</li><li>You will be part of the Software Platforms Teams, working on the development of in-house cybersecurity device software development for Industrial networks.</li><li>You will be building Firewall software for industrial routers which are complex multicore, multi-threaded software systems supporting high-availability, hundreds of network protocols and delivering high throughput packet forwarding.</li><li>Building brand new products, supporting new features, feature enhancements and sustenance of products across the R&amp;D product portfolio, using company’s device software running on company hardware.</li></ul> Requirements: <ul><li>You are a person with passion for coding and creating world class software systems for large organizations.</li><li>A Full time Bachelor/Master of Engineering Degree in Computer Science or equivalent.</li><li>You are able to abstract and use your creativity for disruptive solutions.</li><li>You are fluent in spoken and written English and have the ability or willingness to work in a Global environment</li><li>8 – 12 years’ experience in a product-based organization developing embedded software for Enterprise, Industrial Automation or Service Providers industry.</li><li>Solid understanding of embedded systems architecture, including microcontrollers, microprocessors, and real-time operating systems.</li><li>Ability to work on complex modular software systems, algorithms and be able to design, code, debug and automate software.</li><li>Expertise in C/C++ programming, data structures, Algorithms &amp; debugging tools.</li><li>Expertise in Linux based environment, with extensive knowledge of Linux Internals.</li><li>Hands-on operating systems, IPCs &amp; multi-thread programming experience.</li><li>Advanced working level knowledge of Computer networks and Network protocols in TCP/IP, switching (L2), routing (L3) &amp; security protocols.</li><li>One or more areas like QOS, Segment Routing, Multicast &amp; MPLS.</li><li>Ability to work with existing code base.</li><li>Hands-on experience in Versioning and Git/GitHub/Bitbucket repository.</li><li>Experience with Unit test strategy and execution.</li><li>Experience with Python or equivalent scripting languages</li><li>Experience with packet generating and network test tools.</li><li>Prior experience with any network OS provided by Networking companies like CISCO -IOS/IOS-XE/IOS-XR.</li><li>Designing &amp; understanding of network topologies &amp; deployment.</li><li>Linux containers and dockers.</li></ul>

Responsibilities: <ul><li>Collaborate with team, high availability, concurrent and fault tolerant software systems.</li><li>Significantly contribute to development of Aladdin’s global, multi-asset trading platform.</li><li>Work with product management and business users to define the roadmap for the product.</li><li>Design and develop innovative solutions to complex problems, identifying issues and roadblocks.</li><li>Apply validated quality software engineering practices through all phases of development.</li><li>Ensure resilience and stability through quality code reviews, unit, regression and user acceptance testing, dev ops and level two production support.</li><li>Be a leader with vision and a partner in brainstorming solutions for team productivity, efficiency, guiding and motivating others.</li><li>Drive a strong culture by bringing principles of inclusion and diversity to the team and setting the tone through specific recruiting, management actions and employee engagement.</li><li>For VP Level: In addition to above, a VP level candidate should be able to lead individual projects priorities, deadlines and deliverables using AGILE methodologies.</li></ul> Requirements: Qualifications: <ul><li>B.S. / M.S. degree in Computer Science, Engineering, or a related subject area</li><li>For VP Level: 8+ years of proven experience</li><li>For Associate Level: 4+ years of experience</li></ul> Skills and Experience: <ul><li>A proven foundation in core Java and related technologies, with OO skills and design patterns</li><li>Track record building high quality software with design-focused and test-driven approaches</li><li>Good hands-on object-oriented programming knowledge in Java, Spring, TypeScript, JavaScript, Microservices, Angular (2.0+), React.</li><li>Strong knowledge of Open-Source technology stack (Spring, Hibernate, Maven, JUnit, etc.).</li><li>Experience with relational database and/or NoSQL Database (e.g., Apache Cassandra)</li><li>Great analytical, problem-solving and communication skills</li><li>Some experience or a real interest in finance, investment processes, and/or an ability to translate business problems into technical solutions.</li><li>For VP Level: In addition to the above, a VP level candidate should have experience leading development teams, projects or being responsible for the design and technical quality of a significant application, system, or component. Ability to form positive relationships with partnering teams, sponsors, and user groups.</li></ul> Nice to have and opportunities to learn: <ul><li>Exposure to building microservices and APIs ideally with REST, Kafka or gRPC.</li><li>Experience working in an agile development team or on open-source development projects.</li><li>Experience with optimization, algorithms or related quantitative processes.</li><li>Exposure to high scale distributed technology like Kafka, Mongo, Ignite, Redis</li><li>Experience with Cloud platforms like Microsoft Azure, AWS, Google Cloud</li><li>Experience with DevOps and tools like Azure DevOps</li><li>Experience with AI-related projects/products or experience working in an AI research environment.</li><li>A degree, certifications or opensource track record that shows you have a mastery of software engineering principles.</li></ul>

The Role As a Staff Software Engineer, you will act as a subject matter expert. We are looking for technologists with the highest levels of technical talent, programming, and communication skills with a keen desire to deeply understand our product and how to make our systems stronger and more resilient. &nbsp;Responsibility <ul><li>Lead engineering efforts and team level processes by defining outcomes for others, refining ongoing processes, and providing technical advice to senior leaders on systems, solutions, challenges, and strategy.</li><li>Evangelist for technical standards, engineering best practices, and quality across larger Venmo team , Inc. Determines the technical tasks that other engineers will follow.</li><li>Support end-to-end ownership of design, implementation and operational excellence of software components while proactively improving existing structures and processes.</li><li>Contribute to the technical engineering roadmap by completing quality and thorough assessments of implementation alternatives and their associated trade-offs and providing recommendations.</li><li>Be consistently solutions-focused while contributing to the vision of domain and larger Venmo technical engineering roadmap.</li><li>Exercises judgement in reconciling diverse and competing priorities to identify optimal solutions to problems.</li><li>Leverage strategic thinking and experience to look ahead and anticipate consequences and risks linked to implementation choices; able to identify patterns to reduce repetition into meaningful general solutions.</li><li>A key voice on team-level processes (ex code &amp; design reviews) and oversees projects, ensuring an accurate, complete, timely and operable solution is delivered.</li><li>Serves as an expert to resolve technical inquiries of others.</li><li>Be able to provide technical leadership for a team with limited guidance from management or senior teammates.</li><li>Strong skills interacting and tailoring communication with various technical and non-technical stakeholders, such as product, support, finance operations, compliance and legal.</li></ul> Requirement <ul><li>At least 5+ years’ Experience developing and maintaining consumer-facing mobile applications at scale.</li><li>Strong Kotlin skills &amp; knowledge of multi-threaded, asynchronous code.</li><li>Deep understanding and knowledge around consuming GraphQL and REST APIs from Mobile applications.</li><li>Passionate about mentoring and developing software engineers.</li><li>Strong understanding of testing best practices and familiarity with at least one testing framework for Mobile Development. Skilled at writing Unit and Automation tests.</li><li>Strong knowledge of common design patterns, algorithms, and object-oriented programming with expertise in design patterns such as MVC and MVVM.</li></ul>

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10 algorithms Jobs found

Senior Business Intelligence Analyst

Associate Data Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Director, Data Science

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist

Lead Software Engineer, QA

Java Backend Engineer

Android - Sr/Staff Software Engineer

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10 algorithms Jobs found

Senior Business Intelligence Analyst

Associate Data Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Director, Data Science

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist

Lead Software Engineer, QA

Java Backend Engineer

Android - Sr/Staff Software Engineer

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