Data Scientist (USCB Program)

Experience: 10+ years software engineering; 5+ years Python/R. Would consider # of years experience with PHD in a quantitative discipline.

Overview

CPMC is seeking a Data Scientist who thrives on technically demanding problems involving large-scale computation, complex algorithms, and high‑performance data processing. You will engineer the U.S. Census Bureau’s Disclosure Avoidance System (DAS), a system that executes advanced statistical and differential privacy algorithms across massive datasets.

This role is ideal for an engineer who enjoys:

• Understanding how algorithms behave under realworld scale
• Turning research prototypes into robust, high‑performance systems
• Diagnosing subtle numerical, performance, or correctness issues
• Building distributed systems that must be reproducible, efficient, and scientifically trustworthy

You’ll be building the computational machinery that makes cutting‑edge statistical methods run reliably at national scale.

Key Responsibilities

• Engineer productiongrade implementations of complex statistical and differential privacy algorithms, ensuring correctness, stability, and performance
• Translate research code (Python/R) into optimized, maintainable systems, often requiring algorithmic insight and careful handling of numerical edge cases
• Design and optimize largescale data processing pipelines for ingestion, transformation, validation, and output generation
• Profile, benchmark, and optimize distributed workloads (Spark, EMR, containerized compute) to reduce runtime and cost
• Diagnose algorithmic performance issues—from data skew to solver behavior to memory pressure
• Collaborate deeply with statisticians to understand algorithmic assumptions, constraints, and expected behavior under scale
• Develop reproducible experiment frameworks, including parameter tracking, environment isolation, and deterministic execution
• Build automation and tooling that enable researchers to run large experiments safely and efficiently
• Tune compute and solver configurations (Spark, Gurobi, storage layouts, partitioning strategies) for largescale statistical workloads
• Support distributed execution environments and contribute to DevOps/automation where needed to keep the system reliable

Required Qualifications

• 10+ years professional software engineering experience
• Strong programming skills in Python (primary) and familiarity with R
• Experience with distributed computing (Spark, EMR, or equivalent)
• Strong background in performance engineering, profiling, and debugging complex systems
• Experience building and maintaining largescale data pipelines
• Handson experience with AWS (EMR, S3)
• Experience with CI/CD, automated testing, and environment management
• Familiarity with basic probability and statistics concepts (e.g. hypothesis testing, probability distributions, least squares, etc.)"
• Ability to read, reason about, and improve scientific or researchoriented code

Preferred Qualifications

• Experience collaborating with statisticians or working in scientific computing environments
• Familiarity with numerical methods, statistical computing, or algorithmic evaluation
• Experience with optimization solvers (e.g., Gurobi) or largescale simulations
• Knowledge of differential privacy or privacypreserving computation
• Experience with containerization (Docker, Kubernetes)
• Experience with HPC or large distributed systems

Why This Role Is Technically Unique

• You work on algorithmically complex systems where correctness and performance both matter
• You operate at nationalscale data volumes with strict reproducibility requirements
• You collaborate with researchers pushing the boundaries of statistical privacy
• You solve problems where the bottleneck might be a numerical instability, a distributed shuffle, a solver configuration, a data partitioning strategy, or an algorithmic assumption that breaks at scale
• You directly influence the performance and reliability of a system that protects the confidentiality of Census data

Soft Skills:

• Organizational Skills: Can plan and prioritize work. Follows tasks to their logical conclusion and makes sure that everything has been done to the right standard. Good attention to detail.
• Team Work: Able to enthuse and maintain project interest. Comfortable working both individually and as part of a team. Prepared to challenge ideas within a group in a constructive way.
• Communications: Ability to communicate clearly and efficiently to team members and clients, verbally and in writing. Able to present ideas in a variety of ways depending upon audience and context. Excellent active listening skills.
• Problem Solving: Natural inclination for planning strategy and tactics. Ability to analyze problems and determine root cause, generating alternatives, evaluating and selecting alternatives and implementing solutions.
• Results oriented: Able to drive things forward regardless of personal interest in the task.