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Support sales and account teams by qualifying RFPs, writing proposals, developing pricing, assessing project feasibility, and keeping the CRM updated. Assist in client relationship growth, up-selling, delivery support, partner sourcing, and sales presentations.

Manage and grow a portfolio of Nordic client accounts by building long-term relationships, identifying up- and cross-sell opportunities, executing regional growth strategies, coordinating internal teams to deliver solutions, and maintaining accurate pipeline, forecasting, and CRM reporting to drive sustainable business growth.

As a Senior Machine Learning Engineer, you'll develop and optimize ML models, manage MLOps pipelines on AWS, and collaborate with teams to ensure data quality and model reliability in production.

Manage and qualify RFPs, write proposals, develop pricing, and assess project feasibility using proprietary tools. Maintain CRM, support Account Managers/Directors to grow client revenue through upselling and sales, and assist client services and presentations during project delivery.

Support pre-sales and account activities: qualify RFPs, write proposals, develop pricing, assess project feasibility, keep CRM updated, assist Account Managers in upselling and closing sales, and support delivery and sales presentations.

Support the bid and proposal process by qualifying RFPs, writing proposals, pricing, and assessing project feasibility. Maintain CRM records, assist Account Managers/Directors with client relationship growth, upselling, and delivery support. Help with presentations and partner sourcing as needed.

Support the sales process by qualifying RFPs, writing proposals, developing pricing, and updating CRM. Assist account teams with client relationship growth, project delivery support, presentations, and partner sourcing.

Design and implement user experiences, develop automated deployment solutions, and collaborate within the team on coding and architecture.

The analyst will conduct application testing, risk assessments, develop policies, and ensure compliance with data privacy laws while supporting organizational changes.

Perform data validation, delivery, and tabulation for low-complexity projects. Interpret client requirements, organize and shape data to internal standards, produce outputs, and escalate issues to managers as needed.