ILS-ingenjör hos Saab Dynamics som arbetar med Integrated Logistics Support för avancerade tekniska system.
Responsibilities
Analysera driftsäkerhet, tillgänglighet och underhållsbehov för tekniska system
Ta fram underhålls- och supportkoncept för nya och befintliga produkter
Tolka system- och kundkrav och omsätta dem till lösningar och specifikationer för logistikstöd
Arbeta med reservdelsförsörjning, teknisk dokumentation och utbildningslösningar
Genomföra analyser kopplade till exempelvis driftsäkerhet, underhåll, livscykelkostnader och reservdelsoptimering, såsom FMEA/FMECA, LCC, LORA och reservdelsanalyser
Drive new business opportunities with large, complex accounts in the enterprise segment, qualifying prospects and setting the foundation for Optiv’s sales team to secure strategic cybersecurity solutions.
Locations (2)
Salt Lake City, Utah, United States
Leawood, Kansas, United States
Responsibilities
Collaborate with sales to understand target account segments and cybersecurity service and technology areas of focus
Research target demographics, clients' needs and interests and other data for business development strategies
Oversee lead generation through cold calling, B2B selling and other methods to identify prospects and schedule joint meetings
Analyze market reports to identify new business opportunities
Effectively communicate Optiv’s value proposition and educate clients on partner technologies
Set up and lead a new Data Science team in the Technology department, focusing on advanced semiconductor metrology systems using AI, machine learning, and dephysics-based modelling.
Compensation
£70,000 - £85,000 (depending on experience)
Responsibilities
Lead, develop and mentor the Data Science team while staying hands-on, setting priorities and keeping a fast, evidence-based working rhythm
Own and deliver the Data Science roadmap: synthetic data, modelling, information-limit studies, algorithm development and data analysis tools
Establish the information limit, meaning what is physically extractable given instrument noise, limitations and tip geometry, and use it as the benchmark for every new method
Explore, test and benchmark new algorithms (for example PCA, percentile methods and machine learning) on real and synthetic data, covering achievable performance, measurement uncertainty and gauge capability
Define the handover to Data Analysis in Engineering (prototype code, test data, acceptance criteria and expected performance), and manage the demo and performance data libraries with Applications Development
Lead and optimize marketing operations, manage Marketo and Salesforce integrations, drive data-driven marketing initiatives, and support global marketing teams.
Responsibilities
Own day-to-day management and optimization of Marketo, including building and executing email campaigns, nurturing programs, lead lifecycle processing, automation infrastructure and scoring models.
Partner with marketing stakeholders to support campaign execution, ensuring accurate audience segmentation, QA, testing, and performance tracking.
Manage lead routing, enrichment, and data flow processes across marketing and sales systems.
Establish campaign operations best practices and documentation to drive global consistency and efficiency.
Develop and maintain reporting dashboards to measure marketing performance across channels, campaigns, and funnel stages.
Defines and delivers AI products and capabilities to improve operational efficiency, decision‑making, customer experience, and employee productivity across ProTrans International’s U.S. and Mexico operations.
Responsibilities
Partner with business leaders and users to identify, prioritize, and validate AI use cases
Identify and deliver AI solutions supporting transportation management, shipment visibility and execution, pricing, carrier performance, customer service, exception management, document processing, and operational automation
Translate business problems into product requirements, user stories, acceptance criteria, model inputs and outputs, fallback logic, process changes, and measurable success criteria
Partner with data engineering, analytics, data science, architecture, and security teams to define requirements for data quality, availability, governance, labeling, pipelines, and feedback loops
Design and oversee discovery, experiments, proofs of concept, pilots, controlled rollouts, launch planning, adoption, and continuous improvement
Requirements
Bachelor’s degree in Product Management, Business, Information Technology, Computer Science, Data Science, Engineering, or a related field, or an equivalent combination of education and experience
Design, build and validate the machine learning models behind personalization features in our new mobile trading app, working within guardrails set by the Compliance team.
Responsibilities
Build similar-symbol models (clustering / co-occurrence) on aggregate trading data, including minimum-activity thresholds
Develop propensity models that score customers’ likelihood to adopt new products, from day one of the customer lifecycle
Explore models linking significant price moves to news events
Define features, training data and evaluation metrics; validate models and set score thresholds
Analyze content and in-app engagement data to identify drop-off and high-performing content
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