Data Scientist Senior

Title: Computer Vision Engineers / Data Scientist
Location: Mclean VA M to F (Fully onsite)
Contract role

Must Have Qualifications: 5-7 years of related experience. Strong expertise in Python, SQL, Image analytics, data modeling and snowflake. Financial / mortgage background is required. Experience with Freddie or Fannie is preferred.

Job Title: Data Scientist - Python & Computer Vision

Position Overview

We are seeking a hands-on Data Scientist with strong Python and Computer Vision skills to design, build, test, and operationalize capabilities that convert image-based content and model outputs into usable, reviewable, and analytics-ready data products. This role requires strong software engineering fundamentals, computer vision coding experience, data engineering skills, and the ability to partner across product, modeling, engineering, research, and business teams.

The Data Scientist will contribute to capabilities for image extraction, metadata generation, model-output validation, quality review enablement, and downstream structured data integration. The role is expected to balance Python development, testing, analytical troubleshooting, and delivery execution to help users review, validate, and act on computer vision outputs.

Key Responsibilities

Computer Vision Development & Model Output Engineering

o Develop, enhance, and maintain code that supports computer vision model output processing, image extraction, metadata generation, and validation workflows

o Work with image-based model outputs, bounding boxes, labels, confidence scores, extracted attributes, and structured metadata to support downstream review and analysis

o Build reusable utilities for parsing, transforming, validating, and comparing computer vision outputs across model versions and production-style runs

o Apply strong Python coding practices to automate testing, issue detection, data preparation, and model-output quality checks

Product & QC Workflow Enablement

o Support product capabilities that allow users to review, validate, correct, and quality check model-generated outputs

o Translate computer vision models output into user-facing review patterns, QC screens, exception workflows, and validation experiences

o Partner with UI developers, product owners, and business users to define practical capabilities for model-output inspection and operational review

Test Data, Validation & Quality Engineering

o Create and manage representative test datasets for image extraction, metadata validation, regression testing, and model performance review

o Perform structured testing of model runs across historical and current datasets to identify extraction gaps, metadata issues, formatting errors, and quality concerns

o Validate extracted images, image classifications, and metadata against original PDFs, appraisal reports, and other authoritative source documents to confirm completeness, accuracy, and traceability

o Document defects with clear evidence, expected results, actual results, severity, reproducible examples, and recommended remediation steps

o Retest remediated issues and contribute to repeatable quality gates for model-output readiness

Data Integration, JSON Engineering & Analytics Readiness

o Develop scripts and data pipelines that convert model outputs into structured and semi-structured formats suitable for research, analytics, and downstream consumption

o Support loading and validation of model outputs as JSON Variant or similar semi-structured data formats

o Ensure extracted image attributes, metadata, and model-output payloads are traceable, consistent, and accessible for analysis

Cross-Functional Delivery & Technical Problem Solving

o Collaborate across product management, model development, UI engineering, data engineering, research, business, and delivery teams to operationalize computer vision capabilities within data-driven products

o Investigate technical issues across image inputs, model outputs, metadata payloads, data loads, and user-facing QC workflows

o Communicate progress, risks, blockers, and technical findings clearly to engineering partners and business stakeholders

Required Qualifications

Computer Vision Coding & Software Engineering

o Hands-on experience coding computer vision or image-processing solutions using Python and common libraries such as OpenCV, Pillow, PyTorch, TensorFlow, or similar frameworks

o Strong ability to process image files, extracted labels, model predictions, confidence scores, annotations, bounding boxes, and metadata payloads

o Experience writing modular, maintainable code for automation, validation, transformation, testing, and troubleshooting

Data Engineering & Semi-Structured Data

o Strong SQL and Python skills for working with relational data, semi-structured data, JSON, API outputs, and analytical datasets

o Experience preparing model outputs for downstream systems using JSON, Variant-style data structures, metadata files, or similar formats

o Ability to design validation logic, reconciliation checks, and data quality rules for image-derived outputs

Testing, Debugging & Quality Validation

o Experience testing model-output pipelines, identifying defects, analyzing root causes, documenting issues, and supporting retesting after remediation

o Ability to create representative test datasets and compare expected versus actual computer vision output across runs

o Experience validating extracted image outputs against source PDFs, appraisal documents, supporting files, and other ground-truth reference materials

o Strong analytical skills to detect anomalies, data gaps, misclassifications, format issues, and model-output inconsistencies

Product, UI & Workflow Collaboration

o Experience working with product and engineering teams to support user-facing applications, QC workflows, review screens, or operational tools

o Ability to translate technical model-output structures into practical user, data, and system requirements

o Strong collaboration, communication, ownership, and delivery execution skills in a fast-paced technical environment

Preferred Qualifications

Experience with appraisal images, property photos, mortgage data, or other document/image-heavy business processes

Familiarity with image extraction, object detection, classification, OCR, metadata extraction, or computer vision evaluation techniques

Experience comparing extracted image content and metadata back to source documents to support auditability, traceability, and quality control

Exposure to Snowflake Variant, JSON analytics pipelines, data lake patterns, or research data environments

Experience supporting ***, Client, GSE, financial services, housing, or appraisal-related technology initiatives

Familiarity with UAD, appraisal modernization, model validation, or AI-enabled quality control workflows

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EEO

Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.