Data Scientist - Mumbai, India - JPMorgan Chase Bank, N.A.

JPMorgan Chase Bank, N.A.

Verified Company

Mumbai, India

1 week ago

Posted by:

Deepika Kaur

beBee Recuiter

Description

The

Data Scientist Associates

(Optimization) will have the economics underpinning with a desire to make a large business impact for lines of business/functions with their thought leadership delivering strategic projects using exciting big data environments, econometrics, statistics, and technology solutions. You will have outstanding attention to details, comfortable under ambiguity and affinity for problem solving, evaluating trends and anticipating requirements directly supporting the broader CCB WFP objectives, to ensure clients, partners, stakeholders have the best and most predictive/prescriptive data available for decision making. The Data Scientist Associates shall work together at the intersection of AI, ML, Econometrics, applied scientific computing to ensure Chase maintains the best quantitative models and optimization.

Job responsibilities:

Workforce Planning (WFP) organization is a part of Consumer and Community Banking Operations division.

Workforce Planning Data Science team is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support).

The WFP team supports Chase's call centers, back office, and ~5,200 retail branches.

Projects engaged by the Data Science team can be complex, data intensive, and of a high level of difficulty, each having significant impact on the business.

Typically, these problems will be of an unstructured nature, whereby the employee will be expected to quickly assess and comprehend the situation then develop a practical problem-solving strategy.

You will be expected to analyze the topic in question, develop solution proposals and review their results and next steps with management for prioritization, timing, and delivery.

The data science optimization team is supported by the next-gen data science solutions that move us closer to real-time inference, decision making, and optimizing:

Schedule Optimization
Predictive scheduling and optimization, shift optimization

Operations Research

Branch, call center, backoffice networks simulation, Supply Chain, Inventory Management, Digitization and Whatif scenarios testing

Yield/Revenue Management

Rationalize cost to serve vs service levels, penalty cost modeling meeting contractual agreements at varying degrees of capacity, head count, and schedule impacts

Supply Forecasting

Staffing, service levels, and stress forecasting and outlooks

Required qualifications, capabilities, and skills

Educational Background
Bachelor's Degree or Master's+ with 4+ years of experience with different micro & macro-economic characteristics as an Optimization professional (e.g.

, OR analyst, statistician, industrial engineer, or related professions) in a quantitative field:
Statistics, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, Decision Sciences, and related disciplines.

Technical Skills

Advanced expertise with Queuing theory, linear and nonlinear programming, integer programing, network analysis, replacement problems, sequencing, dynamic problem, pricing elasticity, cost structuring, benefits/loss propositions, and other adhoc strategies such as remediation plans regarding pricing policies, risks, controls
Familiarity with utilitytheory, graph theory based discrete choicemodeling,
Ability to adapt/modify existing or build new statistics models, machine learning models, and/or operations research simulations and models.
Develop and monitor KPIs, metrics, SLAs that attain customer strategies using statistical models, heuristics, and scalable algorithms
Programming languages: Python, R

Ideal Skills

Understand business problems to turn cost to serve profiles into useful analyses and convey recommendations in pricing tactics, margin models engaging with technology counterparts to maximize value even falling short to meet capacity target consistent with defined contract agreements, scheduling gaps, inadequate staff levels.
Communicate complicated concepts and relevant scientific insights from data clearly to business leaders and strong record of executing pricing processes and applied use cases to optimize overall margins, staff allocations to sustain headcount planning & performance
Ability to analyze live customer demand and react to lastminute changes such as inclement weather or operational capacity constraints or any potential staff or scheduling impacts

Preferred qualifications, capabilities, and skills

Implemented or extensive training in machine learning methods (boosted regression trees, random forests, neural networks)
Sophisticated use of data analytics and visualization tools in reporting and influencing
Nice to have exposure in machine learning APIs and computational packages (Tensorflow, PyTorch, Rust, Caffe2, Gluon, Keras, similar framework).
Experience with Tableau Server, Alteryx