Mar 2021 – Present · 5 yrs · United States

• 📘 From Noise To Opportunity: Unlocking Social Media Intelligence With Meaning-Centered Models
• How AI foundation models trained on social data are transforming brand and consumer intelligence. (Forbes, 2025)
• ⚙️ XOps For Enterprise AI: The Convergence Of DevOps, MLOps, LLMOps And AgentOps
• Exploring the future of unified AI operations frameworks for large-scale, secure enterprise deployment. (Forbes, 2025)
• 💡 Accelerating Consumer Electronics With Predictive, Generative And Agentic AI
• A roadmap for OEMs to move from reactive analytics to self-optimizing AI ecosystems. (Forbes, 2025)
• 🏢 Shaping The Future Of Human Resources For Connected Employees With AI
• How AI, automation, and graph-based reasoning are redefining engagement and employee energy. (Forbes, 2024)
• 📈 Boosting Brand Visibility: Harnessing Data Fabric, Machine Learning And GenAI To Increase Share Of Search
• Using Generative AI to drive digital marketing efficiency and real-time share-of-voice growth. (Forbes, 2024)
• 🏗️ Building A World-Class Data Science & Machine Learning Practice
• A practical framework for scaling talent, governance, and value realization in enterprise AI programs. (Forbes, 2024)
• 🌿 Green Generative: A Framework For Sustainable And Effective Generative AI
• Guiding enterprises toward energy-efficient, responsible, and explainable AI development. (Forbes, 2023)

Oct 2020 – May 2022 · 1 yr 7 mos · Bengaluru, Karnataka, India · Hybrid

• Revenue & P&L Leadership
• Drove over 50% revenue growth against a 35% target and managed a profitable $5M+ portfolio with strong margins and disciplined resource utilization.
• New Verticals & Growth Engines
• Launched Manufacturing, Automotive, and Industry 4.0 practices, building a $1M+ pipeline and delivering $500K revenue within three quarters.
• Enterprise AI & Operational Scale
• Led cross-functional AI and data science integration across business units, improving operational efficiency by 18% across delivery and consulting functions.
• Talent & Market Positioning
• Scaled teams 2.5x through strategic hiring and capability building, while elevating SG Analytics’ market profile via industry thought leadership and analyst recognition.

Jul 2018 – Sep 2019 · 1 yr 2 mos · Yokohama, Kanagawa, Japan · On-site

• As part of the core leadership group reporting to the CIO, Chiranjiv shaped and led Nissan’s Data & AI charter during the greenfield build and global scaling of the company’s AI-driven Global Capability Center.
• Data & AI Charter within GCC Leadership
• Owned the enterprise Data Science and AI mandate within the GCC leadership team, defining how data, analytics, and AI would enable Engineering & R&D, Production & Operations, Supply Chain Management, Marketing & Sales, and Finance at global scale.
• Value-Led AI Portfolio across Core Functions
• Designed and executed a prioritized portfolio of applied AI use cases across global plants and business functions, creating a $2.1B opportunity through 5–23% efficiency gains and measurable operational impact.
• Enterprise Data, Platform & Monetization Foundation
• Established data quality, standardization, and AI platform capabilities to support cross-functional reuse, faster deployment, and internal data monetization across regions and functions.
• Global AI CoE & Financial Stewardship
• Built and operated the Global Data Science & AI CoE with P&L responsibility, managing an $18.7M+ budget while balancing in-house teams and strategic partners to drive utilization and scale.
• Customer & Experience Intelligence
• Led AI initiatives across Marketing, Sales, and service functions, improving customer experience and delivering a 28.4% increase in CSAT through predictive and experience-driven intelligence.
• Talent Factory & Enterprise Enablement
• Built and scaled high-performance global data science teams, embedding AI capabilities into business and engineering teams; recognized among India’s Top 10 Data Scientists (2018).

May 2016 – Jul 2018 · 2 yrs 2 mos · Bengaluru Area, India · On-site

• Chiranjiv Led data science strategies to deliver measurable impacts in cross-functional teams. Heading the effort across U.S., Europe, and India, to achieve common data-driven objectives.
• Key Achievements:
• 1) Leading CoE which acts as central authority for the whole Mercedes-Benz Group in the fields of analytics, artificial intelligence and big data. As lead architect of the CoE created systems and structures to allow the technologies to be used throughout the company. (E.g. Ex-Tollo)
• 2) Boosting profitability up-to 15%: Utilizing data analytics resulted in significant reduction of supply chain costs.
• 3) 20% reduction in Operational cost/time: Employed machine learning algorithms to streamline production processes and to optimally assign and utilize resources to improve operational efficiency.
• 4) Developing Strategic IT & R&D Partnerships: Leveraging consulting firms, leading to multi-million-dollar ($120Mn+) collaborations across Germany, the U.S., and India.

Nov 2007 – May 2016 · 8 yrs 6 mos · Palo Alto, CA · On-site

• Industry-Defining Partnerships & Market Leadership
• Orchestrated multi-million-dollar strategic partnerships across CPG, Retail, and Supply Chain, positioning the firm as a pioneer in applied AI and advanced analytics.
• High-Impact Predictive Analytics at Scale
• Designed and deployed predictive analytics solutions across industries, delivering measurable outcomes including 20% improvement in inventory turnover, 15% uplift in targeted marketing effectiveness, and 10% reduction in supply chain transportation costs.
• Revenue & Growth Innovation in B2B and IT
• Created Deal RADAR, an advanced analytics framework to optimize enterprise B2B sales pipelines and recover abandoned deals, generating significant revenue upside; also built predictive services to prevent cloud data-center downtime, achieving top Google rankings and IEEE FedCSIS publication.
• AI Innovation, Patents & Academic Leadership
• Drove applied AI innovation validated through patents and peer-reviewed research, while advancing academic contributions via a Working PhD focused on Applied Machine Learning.

Dec 2002 – Jul 2007 · 4 yrs 7 mos · London Area, United Kingdom · On-site

• Chiranjiv was working as statistician at HSBC's Retail Banking division, leveraging statistical analysis and machine learning to drive customer engagement and revenue growth.
• Key Achievements:
• # 15% increase in cross-selling of key products: Developed a machine learning-based customer segmentation model, resulting precise targeting of HNI customers.
• # Reduced errors by 85%: Initiated automated data cleaning processes that reduced manual errors.
• # ATM hot spot identification: Devised an approach using linear programming and machine learning to identify under-utilized ATM kiosks across the UK. This empowered the retail branch team to repurpose unused ATMs effectively.
• # Best Analyst Award: Received analysts of the quarter award 7 times.