Technical Consultant

As the primary point of contact for key clients, you will be responsible for translating research goals into technical deliverables. Your role will involve ensuring timely and high-quality outputs that are aligned with client expectations and market research standards. Collaboration with research and project managers will be essential to embed stakeholder feedback in deliverables. You will guide and mentor a multidisciplinary team consisting of SQL, R, Python, and Tableau experts to deliver data processing and reporting solutions. Leading sprint planning, resource allocation, and task optimization across concurrent client deliverables will be part of your responsibilities. Elevating team performance through structured review processes and personalized skill development plans is crucial for success. In the long term, your focus will shift towards technical strategy and innovation. You will be tasked with architecting automation and data products to accelerate turnaround time and enhance data integrity. This will involve conceptualizing and building modular backend components using Python, APIs, microservices, and containerized frameworks. Innovation will be driven by integrating LLM-based tools and AI models into existing workflows to improve analytics and decision support. Collaboration with cross-functional teams to prototype, iterate, and refine full-stack solutions will also be part of your role. Additionally, delivering internal training and documentation to democratize automation across the team will be essential. **Required Skills & Qualifications:** **Must-Have:** - 7-10 years of experience in the Market Research tech stack. - Strong leadership skills with a proven track record of delivering end-to-end client projects. - Deep understanding of Forsta Surveys, Qualtrics, SPSS, and various data platforms. - Advanced programming skills in SQL, Python, R, React, and VBA. - Familiarity with Agile methodology and project management tools. **Good to Have:** - Experience in integrating APIs and developing full-stack applications. - Exposure to LLM-based apps such as GPT integration. - Understanding of DevOps practices, Git-based version control, and microservice architecture. - Awareness of PMP or Scrum frameworks.,