KEY ACCOUNTABILITIES
Deliver on business problems:
· Partners with business stakeholders to deliver value add insights and intelligent solutions through ML and AI.
· Collaborates with ML engineers and systems engineers to ensure the models are deployed in a scaled and optimized way. Additionally ensure support the post-production to ensure model performance degrades are proactively managed.
· Expected to be an expert in the business domain spaces to understand and interact with the business stakeholders.
· Provide consultation and review the deliveries for the junior data scientists.
· Recognizes opportunities to apply external industry trends and implements them within role.
· Is considered an expert in at least one of functional areas; brings together business knowledge, resources, people, and technology to create more effective solutions.
Consultation:
· Lead Interactions with stakeholders to learn on problem statement and drive results.
· Be an advocate for data science team.
· Constructively challenge the other data scientists on approach
· Contribute to best practices as we evaluate new platforms, tools and pipelines.
· Mentor Jr. Data Scientist / Interns / Contractors
· Collaborate with analytic leaders across functions.
Stakeholder Management:
· Manage the assigned priorities, consistency of execution and managing resources.
· Develop trust and credibility with business leaders.
· Educate stakeholders on the GCP analytic practices.
· Closely collaborates with the stakeholders on projects and data science leaders to ensure practices are developed and enhanced to support accelerated analytic development and maintainability.
Collaboration:
· Works on problems of diverse scope.
· Demonstrates good judgment in selecting methods and techniques.
· Networks with senior internal and external personnel in own area of expertise.
· Lead research work to new analytic trends aligned to business.
· Demonstrates learning agility and ability to apply to work.
· Leverage and contribute to new open-source innovation.
MINIMUM QUALIFICATIONS
- Minimum qualification- bachelor’s degree (full time)
- Total analytics experience required 10-12 Years.
- Bachelor’s or Master degree in computer science/Statistics/Applied Mathematics/Operations research/Industrial engineering from Tier 1 institute.
- 5+ yrs in a supply chain analytics with strong understanding of supply chain operations inventory management, manufacturing, and distribution
- Proven implementation of ML and AI practices
- Expertise in supervised ML algorithms, OLS regression, naive bayes approach, linear attribution model, time decay model, markov chains along with linear optimization and performance tuning
- Proficiency in FMCG/CPG domain along with experience on cyber security fundamentals is a plus.
- Technical Platform- include proficiency on Google Cloud Platform, SQL, Python and R
- Technical Concepts- MLOps, Containerization, Data Lineage and Visualization
- Experience working with an Agile development methodology featuring sprints, point estimation and daily stand-ups.
- Excellent stakeholder management skills and storytelling skills
- Bachelor’s degree in computer science/Statistics/Applied Mathematics from Tier 1 institute.
AI/ML
- Expertise in supervised ML algorithms, regression, decision trees, ensemble models, time series, forecasting, neural networks
- Proven implementation of ML and AI practices
- Exposure to unsupervised learning and NLP
- Technical concepts and platforms- MLOps, Containerization, Data Lineage and Visualization.
- Proficiency on Cloud Platform( GCP preferable), SQL, Python and R
PREFERRED QUALIFICATIONS
- Knowledge of Advanced AI/Deep Learning techniques