Genpact—Lead Data Scientist 4D

Job description

Description: Lead Data Scientist Ready to turn bold ideas into real-world impact? At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory, our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI, our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment. Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises. Get to know us at genpact.com and on LinkedIn, YouTube, X, and Facebook. Job Description The Solution Architect is accountable for the design and maintenance of a scalable data, analytics and AI solutions which are owned, operated and supported by the Enterprise Analytics team. The Enterprise Analytics team serves Client central functions including Finance, Commercial, R&D, Labs and Innovation. The role partners with a diverse stakeholder landscape, ensuring robust, scalable and enterprise grade analytics solutions are designed and built to directly supports critical business objectives. This role oversees design, delivery and evolution of a portfolio of over 120+ data, analytics and AI solutions used throughout Client company As the Solution Architect in the Enterprise Data & Product Engineering team, your key responsibilities are as follows: TECHNICAL PROFICIENCY AND STRATEGIC CONTRIBUTION - Contribute to and support solution architecture principles, strategies and frameworks across R&D and Commercial. - Drive the development of scalable, standardised architectural patterns across Client functions. - Ensure all solution architecture and development efforts are aligned with the broader business vision and strategic priorities and provide architectural oversight across delivery initiatives. - Collaborate with functional development teams to ensure consistent and integrated use of technologies and patterns across the organization. - Advocate for best practices, tools, and methods related to data, analytics and AI solutions - Contribute towards future state enterprise solution architectures, frameworks, patterns and roadmaps. - Promote awareness and understanding of Enterprise Analytics architectural patterns and frameworks across the organization. - Review and validate high-level architectures and reference architecture libraries LEARNING & GROWTH - Collaborate with the team to learn and apply the best practices in solution architecture. - Actively participate in projects, gaining experience in developing high-quality, scalable, and sustainable data, analytics and AI solutions. - Stay updated with emerging technologies and trends in analytics and AI, contributing to the team's knowledge base by sharing insights and ideas. COLLABORATION & COMMUNICATION - Collaborate closely with data engineers, data scientists, AI engineers and other team members - Foster relationships with both technical and business stakeholders across R&D, Commercial and Finance - Maintain effective communication with the Enterprise Data & Product Engineering Director and Data & Platform Architects, whilst actively participating in team discussions and sharing ideas to improve analytical solution excellence within Client company Scope: The Solution Architect is instrumental in delivering scalable, repeatable and agile analytics solution architectures to unlock and drive business value across Finance, Commercial, R&D, MGS Labs and Innovation: STRATEGIC PARTNERSHIPS · Collaborates closely with associates and teams across MGS functions and Enterprise Analytics to align analytical solution architectures and initiatives with core business objectives and co-create strategic priorities. TRUSTED PARTNER & PROGRAM DISCIPLINE · Acts as an authority for the Enterprise Analytics analytical technology ecosystem, serving as a dependable single point of contact for all related matters. NAVIGATING COMPLEXITY WITH OWNERSHIP · Operates with a high level of autonomy, navigating ambiguity and organisational complexity through a results-driven and proactive approach. ESSENTIAL: - Previous experience as a Solution Architect or Data Architect essential - Strong background in solution and/or platform architecture frameworks, and modern analytical methods and tooling. - Deep understanding of cloud-based data platforms (Azure) and tools (Databricks, SQL, ADF etc) as well as analytics solutions. - Good understanding of Generative (and Agentic) AI architectural concepts and best practices - Excellent stakeholder management and communication skills, with the ability to influence and align across business and technology functions. - Experience building and evolving enterprise solution architectures that scale and adapt to changing business needs. - Knowledgeable in Data Source systems (eg. SAP), Reporting Technologies (PowerBI) and Data Lake technology - Strong interpersonal skills - Fluent in writing and speaking English SOLUTION DESIGN INVOLVEMENT & OWNERSHIP - Reference Architectures: Contribute to and maintain reusable architectural patterns - High-Level and Low-Level Designs (HLDs): Generate, iterate and review HLDs and LLDs for product owners and development teams - Key Design Decisions (KDDs): Own architectural decisions for your solutions in alignment with the Architecture Review Board and beyond - Architecture Option Assessments: Lead decisioning on tooling, modelling, and patterns for data, analytics and AI solutions. Qualifications Bachelors - Business Analytics, Bachelors - Computer Science, Bachelors - Statistics, Masters - Data Science Certifications Data Science Using R - SimpliLearnSimpliLearn Required Skills Adaptive Technology, Agile Methodology, Artificial Intelligence (AI), Change Management, CI/CD, Client Relations, Collaboration Tools, Data Provisioning, Data Validation, Design Thinking Language English Language Proficiency - Proficient - C2 Additional Job Location - Job Type Regular Master Skill List - Advanced Analytics / AI / ML Remote Type - Office Work Shift - Flex Time (India) Why join Genpact? • Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter • Make an impact – Help global enterprises solve business challenges that matter • Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead • Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day • Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.