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
- 10–12 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.
