KEY ACCOUNTABILITIES
Deliver on Business Problems
- Partner with business stakeholders to deliver value-add insights and intelligent solutions through ML and AI
- Collaborate with ML engineers and systems engineers to deploy models in a scaled and optimized way
- Ensure model performance degradation is proactively managed post-production
- Be an expert in the business domain to interact effectively with stakeholders
- Provide consultation and review deliveries of junior data scientists
- Recognize opportunities to apply external industry trends
- Be considered an expert in at least one functional area, combining business knowledge, resources, people, and technology to create solutions
Consultation
- Lead interactions with stakeholders to understand problem statements and deliver results
- Advocate for the data science team
- Constructively challenge other data scientists on their approach
- Contribute to best practices around new platforms, tools, and pipelines
- Mentor junior data scientists, interns, and contractors
- Collaborate with analytic leaders across functions
Stakeholder Management
- Manage assigned priorities and ensure consistency in execution and resource management
- Develop trust and credibility with business leaders
- Educate stakeholders on GCP analytics practices
- Collaborate closely with stakeholders and data science leaders to enhance development and maintainability
Collaboration
- Work on problems of diverse scope using sound judgment in selecting methods
- Network with senior internal and external experts in the field
- Lead research work in new analytics trends aligned to business
- Demonstrate learning agility and apply it to work
- Leverage and contribute to open-source innovation
MINIMUM QUALIFICATIONS
(Expertise in Section-2 and Exposure to Section-1)
Section 1 Expertise in AI/ML or Operations Research
- Expertise in supervised ML algorithms such as regression, decision trees, ensemble models, time series, forecasting, and neural networks
- Proven implementation of ML and AI practices
- Exposure to unsupervised learning and NLP
- Knowledge of MLOps, containerization, data lineage, and visualization
- Proficiency in Google Cloud Platform, SQL, Python, and R
Operations Research
- Experience constructing and solving linear, mixed-integer, constraint, and nonlinear programming problems
- Hands-on experience solving large-scale optimization problems with runtime and memory efficiency
- Ability to design and implement heuristic algorithms
- Experience with network optimization, cutting stock, and knapsack-type problems
- Hands-on experience with OR tools like Python, Google OR tools, IBM ILOG CPLEX, Gurobi, AIMMS, and FICO Express
Other Expertise and Experience
- Bachelor's degree (full-time) required
- 1012 years of total analytics experience
- Bachelor's or master's in Computer Science, Statistics, Applied Mathematics, Operations Research, or Industrial Engineering from Tier 1 institute
- 5+ years of supply chain analytics experience with strong understanding of inventory management, manufacturing, and distribution
- Proficiency in FMCG/CPG domain
- Experience with Agile methodology (sprints, point estimation, daily standups)
- Excellent stakeholder management and storytelling skills
