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Infosys · 21 hours ago

Pricing Data Science Principal Consultant

Hartford, CT

Full-time

Hybrid

Lead/Staff

11+ years exp

Infosys is seeking an innovative and experienced Principal Consultant specializing in Pricing Data Science to join our team. The ideal candidate will leverage advanced analytics, machine learning, and data-driven strategies to optimize pricing models, drive revenue growth, enhance profitability, and improve market share for our clients.

ConsultingInformation ServicesInformation TechnologyIT ManagementSoftware

No H1B

Responsibilities

Collaborate with clients to understand business objectives, challenges, and opportunities within the supply chain domain

Design and implement data science strategies aligned with client goals to enhance supply chain performance

Serve as a trusted advisor, providing thought leadership in supply chain analytics and data-driven decision-making

Design and guide team on developing advanced analytics solutions, including predictive modeling, machine learning algorithms, and optimization techniques

Utilize big data platforms, statistical software, and programming languages to analyze supply chain data and generate actionable insights

Ensure the robustness, scalability, and accuracy of developed models and tools

Lead cross-functional teams in delivering end-to-end projects on time and within budget

Manage project scope, timelines, and deliverables while ensuring high-quality outcomes

Develop clear communication and reporting strategies to keep stakeholders informed and engaged

Present data-driven insights and recommendations to executive-level stakeholders

Build and maintain strong client relationships, ensuring long-term collaboration and value creation

Conduct workshops and training sessions to upskill client teams on data science capabilities

Stay abreast of emerging trends and technologies in supply chain management and data science

Contribute to white papers, webinars, and industry conferences to establish the company’s reputation as a leader in pricing analytics

Identify opportunities for innovation and continuous improvement within the pricing domain

Qualification

Pricing Data ScienceMachine LearningRevenue OptimizationData AnalysisPricing MethodologiesProject ManagementClient EngagementCommunication SkillsTeam Leadership

Required

Candidate must be located within commuting distance of Richardson, TX or Raleigh, NC or Phoenix, AZ or Indianapolis, IN, or Hartford, CT or be willing to relocate to the area

Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education

Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time

At least 11 years of experience with Information Technology

Experience with a focus on pricing, promotion, revenue optimization, including leadership roles

Hands-on experience in analyzing pricing, promo data and advising clients on pricing and promotion decisions

Strong understanding of pricing methodologies, revenue management principles, price benchmarking, and competitive pricing analysis

Ability to understand and conceptually design analytics algorithms for pricing and promotion

Proficiency in price sensitivity analysis, cost-plus pricing, value-based pricing, promotional effectiveness analysis, and tiered pricing strategies

Preferred

At least 9 years of experience with a focus on pricing, promotion, revenue optimization, including leadership roles

Familiarity with subscription-based pricing models, bundling strategies, and revenue forecasting model etc. Experienced in Agile way of working, manage team effort and track through JIRA

Advanced degree (Master's or Ph.D.) in Data Science, Economics, Statistics, Operations Research, Business Analytics, or a related field is preferred

Exceptional communication and presentation skills, with the ability to convey complex concepts to non-technical audiences