Top 2 Senior digital signal processing engineer Jobs in Columbus

Director of Product Development
EASE LOGISTICS SERVICES LLC —Dublin, OH
- Full-time
- Azure
- Computer Science
- Master's degree
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JPMorganChase —Columbus, OH
- Full-time
- 5 years
- Product management
- Mentoring
- Health insurance
- Tuition reimbursement

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Director of Product Development
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Bachelor’s degree in computer science, data science, software engineering, information technology, or related technical field required.
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Director of Product Development

EASE LOGISTICS SERVICES LLC
Dublin, OH

Quick Apply

Job Details

Full-time

Qualifications

AI models
Systems integration
Software engineering
Contractor management
Requirements design
Managing IT teams
Managing data teams
Enterprise software systems development
Microservices
Production systems
Machine intelligence
Bachelor's degree
Technology management
Model deployment
Vendor relationship management
Cloud Native Design
Requirements management
Vendor negotiation
Engineering product development
Agile software development
Machine learning (ML) fundamentals
Business requirements
Strategic partnerships
Project stakeholder communication
Stakeholder relationship building
Cross-functional communication
Technical product management experience within tech
Agile planning
Senior leadership
Stakeholder management

Full Job Description

ESSENTIAL DUTIES

Product Vision & AMMI Platform Leadership

Own the product vision, strategy, and multi-year roadmap for AMMI, ensuring it evolves into an industry-leading, AI-enabled logistics toolkit.
Define and prioritize the product backlog based on SPEED impact, business value, customer need, and technical feasibility.
Serve as the internal champion for AMMI—articulating the platform’s value to internal stakeholders, leadership, and external partners.
Establish product governance and sprint cadence frameworks that align development velocity with enterprise priorities.
Translate the EASE growth strategy into a phased, deliverable-driven product roadmap with measurable outcomes tied to SPEED, customer retention, and operational leverage.
Drive product discovery and user research processes to ensure AMMI capabilities are built in response to real operational needs and market opportunities.

AI Strategy & Innovation

Co-own EASE’s enterprise AI strategy alongside the CSO, establishing a clear framework for how AI capabilities are identified, evaluated, integrated, and measured.
Lead the identification, evaluation, and management of AI vendors and technology partners, ensuring EASE maintains access to cutting-edge capabilities.
Build AMMI as a genuinely AI-native platform—embedding machine learning, predictive analytics, intelligent automation, and decision-support capabilities throughout the product stack.
Champion an experimental mindset across the product and development organization: hypothesis-driven development, rapid prototyping, structured pilots, and data-informed iteration.
Stay ahead of emerging AI trends in logistics and adjacent industries, translating market signals into actionable product investments.
Establish EASE’s internal AI governance framework, including model performance standards, responsible AI practices, and adoption measurement.

Build, Buy, & Partner Decisions

Own the build/buy/partner decision framework for new product capabilities, working closely with the CSO to evaluate the optimal path to each new capability.
Lead structured assessments of third-party solutions, open-source tooling, and partner integrations as alternatives or complements to internal development.
Evaluate and manage AI and technology vendor relationships, including capability assessments, commercial negotiation, performance accountability, and integration roadmaps.
Ensure all vendor and partner engagements are governed with clear SLAs, ROI expectations, and strategic alignment criteria.
Maintain a living technology partnership roadmap that reflects current integration priorities, partner performance, and evolving strategic fit.

Resource Strategy & Team Leadership

Lead and develop a high-performing internal product and engineering team, setting clear expectations, fostering a culture of accountability, and enabling team members to grow.
Design and implement a blended development resource model that strategically combines in-house talent with external development capacity to accelerate delivery and manage cost.
Manage external product development relationships, including performance oversight, scope management, and quality assurance, ensuring external teams operate as seamless extensions of the internal team.
Define onboarding standards, development norms, and collaboration practices that unify internal and external contributors under a shared operating model.
Partner with Finance and the CSO to manage the product development budget, forecasting capacity needs and balancing investment across internal headcount and external resources.

Data Science & Analytics

Own EASE’s data science capability, building internal expertise and platform infrastructure that transforms raw logistics data into predictive insight and autonomous action.
Lead the design and development of ML models, intelligent pricing tools, operational forecasting capabilities, and other data-driven product features within AMMI.
Establish a data product strategy that treats EASE’s proprietary data as a strategic asset—defining how it is captured, structured, surfaced, and operationalized.
Champion the use of data and experimentation in product decision-making, embedding A/B testing, analytics instrumentation, and model performance monitoring into the development lifecycle.
Ensure data science work is tightly connected to operational outcomes, with a clear line from model or feature to SPEED impact.

Pricing Science & Predictive Cost Modeling

Own the design, development, and continuous improvement of EASE's pricing science systems, including predictive cost models, dynamic rate engines, and margin optimization tools embedded within AMMI.
Lead the development of carrier cost prediction and lane-level pricing models that enable EASE to price with speed, accuracy, and confidence across all freight modes and markets.
Build and maintain a feedback loop between operational outcomes and pricing models—continuously retraining and improving model accuracy using real shipment, cost, and margin data.
Partner with Sales, Operations, and Finance to ensure pricing science capabilities are integrated into quoting workflows, sales tools, and executive reporting.
Build product capabilities that support and accelerate the RFP response process—enabling cost estimates to be generated faster, with greater accuracy, and with reduced manual processing effort.
Establish model performance standards, drift monitoring, and governance practices that ensure pricing models remain accurate, explainable, and aligned with business objectives.

SPEED Ownership & Product Performance

Treat SPEED (Shipments Per Ease Employee Daily) as the defining product KPI—ensuring every feature, release, and investment decision is evaluated against its anticipated contribution to SPEED.
Define product OKRs and delivery metrics that create a clear feedback loop between product development activity and measurable business outcomes.
Establish release cadence and product performance review processes that drive continuous improvement and hold the roadmap accountable to quarterly targets.
Partner with Operations and Sales to validate that new capabilities are adopted effectively and delivering intended value in the field.
Report to the CSO and executive leadership on product performance, roadmap progress, development velocity, and SPEED contributions.
Develop and maintain win/loss analytics capabilities within AMMI that give Sales and leadership accurate, timely insight into bid outcomes, pricing competitiveness, and revenue conversion patterns.

Cross-Functional Collaboration

Partner closely with the VP, Technology to ensure seamless alignment between new product development and the underlying systems, infrastructure, and internal tools that support them.
Collaborate with Sales, Customer Operations, and Marketing to ensure AMMI capabilities are understood, positioned, and adopted effectively.
Serve as a bridge between the technical and business domains—translating complex product and AI concepts into clear commercial and operational narratives for non-technical stakeholders.
Contribute to EASE’s go-to-market strategy by providing technical and product depth for sales enablement, RFP responses, and customer engagements where AMMI is a differentiator.
Partner with Sales and Operations to embed RFP response tooling into AMMI workflows, reducing the time and manual effort required to produce competitive, data-backed bids.

KPIs, Performance & Measurement

Define, monitor, and enforce accountability for KPIs related to system performance, uptime, project delivery, security, and deliverable outcomes.
Responsible for tracking product budget, forecasting, and spend.
Use data-driven insights to guide decision-making and continuous improvement.

LEADERSHIP AND SUPERVISORY RESPONSIBILITIES

Lead and mentor the Product Development function, including internal engineers, product managers, data scientists, and external development resources.
Establish a high-accountability team culture grounded in EASE’s manifesto: execution is necessary, results are mandatory.
Create and maintain clear performance expectations, sprint cadences, and delivery commitments for all product development resources.
Partner with the executive team to ensure product strategy is tightly integrated with corporate strategy, commercial priorities, and operational goals.
Submit monthly leadership reports no later than the 7th calendar day of the following month.
Provide regular reporting to the CSO and executive leadership on product roadmap status, development velocity, resource utilization, and SPEED impact.
Build organizational capability by developing internal talent and structuring the team for scale as EASE grows.

Responsible for tracking product budget, forecasting, and spend.
Establish KPI’s for each individual on the product development team, establish AI adoption KPI’s to ensure and track ROI on projects and deliverables.

QUALIFICATIONS:

Education

Bachelor’s degree in computer science, data science, software engineering, information technology, or related technical field required.
Master’s degree in computer science, data science, artificial intelligence, or related technical field is strongly preferred.
Relevant product management, AI/ML, or cloud certifications are a plus.

Experience

10+ years of progressive experience in product management, product development, or software engineering, with at least 3–5 years in a senior leadership role.
Demonstrated success building and scaling modern software products in production environments, ideally in logistics, supply chain, transportation technology, SaaS, or adjacent industries.
Proven experience developing and deploying AI/ML-powered products, including hands-on familiarity with model development workflows, ML Ops practices, and AI integration patterns.
Experience leading blended development teams that include both in-house engineers and external product development resources or offshore/nearshore vendors.
Track record of managing and delivering complex, multi-workstream product roadmaps in a high-growth, fast-paced operating environment.
Experience with cloud-native product development (AWS, Azure, or GCP) and modern software architecture patterns (microservices, APIs, event-driven systems).
Experience with data science team leadership, including ML model development, data pipeline management, and analytics product delivery.
Demonstrated ability to translate business strategy into product requirements and measurable outcomes.
Experience managing AI and technology vendor budgets and relationships, including commercial negotiation, SLA accountability, and integration oversight.

Knowledge, Skills, & Abilities

Deep understanding of modern software development practices, including agile/scrum methodologies, CI/CD pipelines, and product-led development frameworks.
Strong command of AI/ML technologies, including large language models, predictive analytics, automation tooling, and data science platforms.
Familiarity with logistics technology ecosystems, including TMS, WMS, EDI, and digital freight platforms, is highly preferred. McLeod TMS experience preferred.
Ability to architect and manage a blended internal/external development model, with strong vendor and contractor management skills.
Strong analytical, problem-solving, and data-driven decision-making capabilities, with experience establishing product KPIs and measurement frameworks.
Excellent leadership, communication, and cross-functional stakeholder management skills.
Entrepreneurial mindset with a bias for action, comfort with ambiguity, and the ability to operate effectively in a high-accountability environment.
Strong ability to translate complex technical concepts into clear, commercially-oriented narratives for non-technical audiences.
Mindset of continuous improvement and a genuine passion for building products that deliver
Ability to translate complex technical information into actionable business strategies.
Excellent leadership, communication, and stakeholder management skills.
Strong communication and interpersonal skills, with the ability to work effectively in a team environment.
Ability to prioritize tasks and manage time effectively in a fast-paced environment.

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