Applied Scientist II, Analytics Technology and Engineering
1 month ago
ATE(Analytics Technology and Engineering) team is responsible for creating core analytics, science capabilities, platforms development and data engineering. We develop scalable analytics applications and research modeling to optimize operation processes.. You will work with professional software development managers, data engineers, data scientists, applied scientists, business intelligence engineers and product managers using rigorous quantitative approaches to ensure high quality data tech products for our customers around the world
We are looking for an Applied Scientist to join our growing Science Team in Bangalore. As an Applied Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. You will be responsible for building ML models to solve complex business problems and test them in production environment. The scope of role includes defining the charter for the project and proposing solutions which align with org's priorities and production constraints but still create impact . You will achieve this by leveraging strong leadership and communication skills, data science skills and by acquiring domain knowledge pertaining to the delivery operations systems. You will provide ML thought leadership to technical and business leaders, and possess ability to think strategically about business, product, and technical challenges. You will also be expected to contribute to the science community by participating in science reviews and publishing in internal or external ML conferences.
Our team solves a broad range of problems that can be scaled across ROW (Rest of the World including countries like India, Australia, Singapore, MENA and LATAM). Here is a glimpse of the problems that this team deals with on a regular basis:
•Using real time day signals to give ahead volume forecasting for last mile and middle mile for labour planning
•proactively identifying the network fraud across various Ops entities
•Building graphs based algorithms to determine collusion between Customer, Seller and Ops entities
•Using LLMs to automate operations processes and working with multiple WW Science teams to bring product parity.
•Using machine learning models and optimization algorithms to find optimal prices for Amazon middle-mile transportation
•Using OR to design Automated planner and scheduler product. It takes forecast, site constraints, CPT/CIT, vehicle availability, transit times etc. as inputs and provides vehicle departure timings, optimal route as output to optimise truck fill rate and loaded distance travelled. One of the key requirement for Coltan to provide vehicle departure time is time of day forecast.
Key job responsibilities
- Lead one or two large scale high-impact projects
- Implement SOTA and complex ML solutions to meet the org goals
- Publish work in internal and external top-tier conferences
- Provide inputs in team growth and goal planning
- Educate peers/team on science best practices
- Expand the use of ML within the organization.
As part of our team, candidate in this role will work in close collaboration with other applied scientists and cross functional teams on high visibility projects with direct exposure to the senior leadership team on regular basis.
About the team
This team is responsible for applying science based algo and techniques to solve the problems in operation and supply chain. Some of these problems include, volume forecasting, capacity planning, fraud detection, scenario simulation and using LLM/GenAI for process efficiency
We are open to hiring candidates to work out of one of the following locations:
Bengaluru, KA, IND
BASIC QUALIFICATIONS
- 4+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
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