Data Scientist Senior Associate

JPMorgan Chase; Plano (TX); On-site; USD 85,000 - 105,000; Full time

Benefits offered by this job

Comprehensive health care coverage

Retirement savings plan

Tuition reimbursement

Job summary

JPMorgan Chase in Plano, Texas is seeking a Data Scientist Associate to develop data-driven approaches for staffing decisions in the Consumer Bank Sales Science team. Responsibilities include maintaining branch staffing models, designing strategies for productivity improvements, and collaborating across various departments to implement solutions.

Ideal candidates should have 1-3 years of relevant experience and strong skills in Python and SQL. They will enrich the team with diverse talents focusing on analytics and data science.

Qualifications

• 1-3 years of experience in data science applied to business problems.
• Ability to write clean, testable code in Python and SQL.
• Solid foundation in statistics and predictive modeling.

Responsibilities

• Develop and maintain staffing models for branch optimization.
• Design staffing strategies and quantify their impact.
• Build scenario-planning tools for decision-making.

Skills

Python

SQL

Statistics

Predictive modeling

Tools

Spark

Git

Job description

As a Data Scientist Associate in the Consumer Bank Sales Science team, you will help develop and scale data-driven approaches that connect customer demand, branch capacity, and sales outcomes to inform staffing decisions across our branch network. You'll work on analytically rich problems-forecasting demand, modeling capacity, and evaluating tradeoffs-to help teams make decisions that improve customer experience and business performance. You'll partner closely with colleagues across branch operations, workforce management, finance, product, and analytics to translate real-world constraints into solutions that can be put into practice. You'll communicate insights clearly to both technical and non-technical stakeholders and help build repeatable tools and measurement frameworks. You'll have opportunities to expand your technical depth and broaden your business impact through mobility across adjacent analytics and data science problem spaces within the firm.

Key responsibilities

• Develop and maintain branch staffing models to optimize banker allocation, leveraging capacity modeling, demand forecasting, and constraint-based optimization techniques.

• Design and evaluate staffing strategies (coverage, schedules, skill mix) and quantify expected impact on sales performance, customer outcomes, and productivity.

• Build scenario‑planning tools to support “what‑if” decisions on branch footprint, traffic changes, operating hours, and banker role design.

• Establish KPI frameworks and reporting to monitor staffing interventions (e.g., conversion, appointment utilization, wait‑time proxies, productivity, customer experience).

• Lead analytical assessments and experiments/pilots to measure the effectiveness of staffing changes and translate results into clear recommendations and actions.

• Partner with data and platform teams to source, curate, and document datasets; create reusable feature sets/pipelines to enable repeatable analytics and model deployment.

• Collaborate with cross‑functional stakeholders (branch operations, workforce management, sales leaders, product partners) to align requirements and communicate insights to technical and non‑technical

Required qualifications

• 1-3 years of experience (or strong internship/co‑op experience) applying data science to business problems.

• Strong programming skills in Python and SQL ; ability to write clean, testable code.

• Solid foundation in statistics and predictive modeling (regression/classification, time series basics, model evaluation).

• Experience translating ambiguous problems into analytical approaches and communicating results clearly.

Preferred qualifications

• Experience with optimization (linear/integer programming, heuristics) and/or forecasting (hierarchical or time‑series models).

• Familiarity with operational analytics concepts (capacity, queues, service levels, workforce planning).

• Experience with model deployment patterns (batch scoring, APIs), MLOps fundamentals, and version control (Git).

• Experience with large‑scale data environments (e.g., Spark) and dashboarding/visual analytics tools.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans