Top Tech Jobs & Startup Jobs in Charlotte, NC

Develop and optimize AI and machine learning algorithms, models, and scalable Python systems. Transform raw data into actionable insights, apply machine learning libraries and NLP techniques, improve data quality, and deliver automation solutions for clients. The role also involves complex data analysis, stakeholder collaboration, client relationship management, and navigating ambiguous business challenges.

Leads strategy consulting initiatives for pharmaceutical and life sciences clients, focusing on customer experience, journey mapping, segmentation, customer data management, and engagement strategies. Manages client accounts, project planning, budgets, execution, stakeholder relationships, quality, and timelines. Coaches and mentors consulting teams while identifying opportunities for business growth and driving data-informed customer-centric improvements.

Lead and manage large-scale Oracle Cloud/Fusion implementation programs: define scope, develop project plans, allocate resources, monitor progress, mitigate risks, engage stakeholders, oversee program/portfolio management, and coach teams to deliver Oracle ERP solutions and drive continuous process improvement.

Develop and implement marketing technology and digital strategies for clients, analyze campaign performance, manage CRM processes, and optimize customer engagement. Lead digital merchandising, content marketing, product positioning, pricing strategies, and marketing operations. Build client relationships, prospect for business opportunities, mentor junior team members, and deliver technology-enabled solutions aligned with business objectives.

Manage commercial and internal product lifecycles from strategy and definition through production, release, and end-of-life. Develop product strategies, conduct market and customer research, analyze competitors and data, and inform roadmap decisions. Collaborate cross-functionally to drive innovation, commercialization, and business growth while applying Agile methodologies. Build client relationships, support team development, navigate ambiguity, and deliver recommendations aligned with business objectives and professional standards.

Provides strategy consulting for pharma and life sciences clients, focusing on customer analytics and experience. Responsibilities include analyzing client needs, designing customer journey maps, managing segmentation and satisfaction surveys, interpreting customer data, developing value propositions, identifying improvement opportunities, and guiding teams in implementing customer experience strategies. The role also involves client relationship development, business process improvement, trend analysis, and delivering strategic recommendations that improve customer satisfaction, engagement, loyalty, and business growth.

Leads strategic tax planning, R&D tax credit advisory, tax compliance, and restructuring projects for clients. Directs and coaches teams, ensures professional standards and independence requirements, identifies tax opportunities, communicates recommendations, incorporates client feedback, and fosters high-performing, inclusive teams.

Analyze complex datasets, develop data models, dashboards, and visualizations, and conduct predictive and statistical analysis for client decision-making. Collaborate with clients to deliver tailored analytics solutions, maintain data integrity, communicate insights through reports and presentations, and support data-driven operational strategies using SAS, Power BI, Tableau, and SQL tools.

Leads healthcare operations consulting engagements by analyzing client needs, developing operational strategies, improving processes, managing transformation projects, and using analytics to enhance performance. Oversees planning, budgeting, resources, stakeholder engagement, and service delivery while coaching teams, managing conflicts, supporting change initiatives, and identifying business opportunities.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.