Associate Vice President

About SG Analytics

SG Analytics is a leading data, analytics, and AI services firm delivering end-to-end consulting and delivery solutions to global clients. Our Data, Analytics & AI vertical partners with enterprises to unlock value through advanced analytics, machine learning, and AI-driven transformation. We are seeking a dynamic and entrepreneurial leader to drive inside sales, solutioning, and delivery excellence for this high-growth vertical.

Role Overview

As AVP / VP Data, Analytics & AI, you will be the anchor of our vertical's growth engine owning the full lifecycle from pipeline creation and client solutioning through to delivery oversight. You will work at the intersection of business development, pre-sales, and project delivery, bringing together technical depth and executive presence to win, grow, and retain clients. This is a high-visibility, high-impact role with direct influence on revenue, talent, and strategic

Key Responsibilities

1. Delivery Management

• Lead end-to-end delivery of advanced analytics and machine learning projects, ensuring quality, timeliness, and alignment with client objectives.
• Establish robust delivery governance frameworks including milestone tracking, risk management, and client escalation protocols to safeguard engagement health.
• Partner with technical leads and data science teams to review solution architecture, model outputs, and deployment strategies, ensuring best-in-class outcomes.
• Drive consistent revenue margin realisation by balancing resource utilization, scope management, and operational efficiency across active engagements.
• Serve as an executive sponsor for key accounts, fostering long-term relationships and identifying opportunities for account expansion.

2. Solution Development & Pre-Sales

• Translate client business challenges into compelling, differentiated analytics and AI solutions spanning data engineering, predictive modelling, NLP, computer vision, and generative AI.
• Lead the design and articulation of proposals, RFP responses, and proof-of-concept frameworks that drive lead conversion and demonstrate measurable business value.
• Collaborate with business development and account teams to develop pricing strategies, SOW structures, and solution roadmaps tailored to client verticals.
• Represent SG Analytics in client workshops, discovery calls, and executive presentations confidently positioning our capabilities against competitive alternatives.
• Build reusable solution accelerators, case studies, and thought leadership assets that shorten the sales cycle and strengthen the brand.

3. Inside Sales & Business Development

• Own and drive the inside sales pipeline for the Data, Analytics & AI vertical from lead qualification and opportunity assessment through to deal closure.
• Proactively identify and pursue upsell and cross-sell opportunities within the existing client portfolio, maintaining high client satisfaction scores.
• Engage with prospects through outbound outreach, webinars, industry events, and direct consultative selling, building a strong personal brand in the analytics community.
• Set and track inside sales KPIs in alignment with vertical revenue targets, reporting progress to senior leadership on a regular cadence.

4. Team Leadership & People Development

• Build, mentor, and retain a high-performing team of analysts, data scientists, and engagement managers, fostering a culture of accountability and continuous learning.
• Define clear performance objectives, conduct regular reviews, and create structured career development pathways aligned with individual aspirations and business needs.
• Ensure adequate resource planning and allocation across concurrent engagements, proactively managing capacity constraints to protect delivery quality and margins.
• Champion knowledge sharing across the vertical through structured communities of practice, internal training, and peer learning initiatives.

5. AI-Driven Innovation & Efficiency

• Actively leverage generative AI, LLM-based tooling, and AI-assisted development frameworks to accelerate delivery cycles, reduce manual effort, and improve output quality.
• Identify and embed AI-powered efficiency tools across delivery workflows from automated reporting and insights generation to intelligent QA and code review.
• Stay at the forefront of emerging AI developments and translate them into practical, client-ready service offerings that differentiate SG Analytics in the market.
• Cultivate an innovation mindset within the team, running structured ideation sprints and pilot programmes to test new AI-driven approaches.

Qualifications & Experience Essential

• 1012 years of progressive experience in the analytics and AI industry, with a track record spanning consulting, delivery, and client engagement.
• Demonstrated experience in pre-sales or solutioning ability to craft and present technically credible, commercially compelling proposals.
• Prior leadership experience managing cross-functional delivery teams of 10+ professionals across analytics and data science disciplines.
• Proven record of owning or significantly contributing to revenue targets in a consulting, professional services, or technology environment.
• Hands-on technical proficiency in Python, R, SQL, and/or relevant ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch); comfort reviewing code and model outputs.
• Deep familiarity with the modern data and AI stack cloud platforms (AWS, Azure, GCP), data engineering tools, MLOps practices, and BI/visualisation technologies.
• Strong understanding of advanced analytics techniques: predictive modelling, NLP, recommendation systems, forecasting, and anomaly detection.

Preferred

• MBA or advanced degree in a quantitative discipline (Statistics, Computer Science, Engineering, Data Science) from a reputed institution.
• Experience working with global clients across industries such as BFSI, retail, CPG, healthcare, or technology.
• Exposure to generative AI and LLM-driven product or service development.
• Relevant certifications in cloud platforms, data engineering, or AI/ML disciplines.