Data Scientist

Phillips, Inc.
United States
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$120,000 - $160,000
Working hours
Regular working hours

Tech stack

Microsoft Excel Data Analysis Data Dictionary Data Visualization Document-Oriented Databases Python (Programming Language) Power BI Standard Sql Tableau (Software) Model Validation Git Data Analytics
+3 more
Machine Learning Operations Looker Analytics Software Version Control

Job description

Location: Remote. The successful candidate must be based in the US, and able to work Eastern Standard hours., * Develop predictive and prescriptive models used to forecast collections and support portfolio acquisition and business strategy decisions.

  • Deploy, monitor, or maintain predictive or prescriptive models in production environments.
  • Support analysis and models for portfolio acquisition opportunities.
  • Apply statistical and machine learning techniques to improve hybrid forecasts.
  • Design, build, and maintain robust data pipelines, transformations, and analytical workflows using SQL, Python and/or R.
  • Contribute to scalable data models and schemas to support portfolio valuation, forecasting, reporting, and operational analytics.
  • Implement data quality rules, validation logic, automated QA checks, and monitoring frameworks to ensure data integrity.
  • Perform exploratory data analysis to identify trends, data gaps, and metric behavior related to portfolio performance.
  • Translate business questions and acquisition strategy into technical requirements, datasets, and analytical solutions.
  • Create reports, dashboards, and analytical outputs that are usable and interpretable by non-technical stakeholders.
  • Collaborate closely with analytics, engineering, and business partners to align data definitions, metrics, and logic.
  • Document data pipelines, models, transformations, business rules, and data dictionaries to support governance and continuity.

Requirements

  • Minimum of 5 years of experience in data science or data analytics roles.
  • Advanced Excel and SQL skills with hands-on experience building scalable transformations and data models.
  • Proficiency in Python and/or R for analytics, automation, and modeling.
  • Experience developing forecasting, valuation, pricing, or portfolio performance models.
  • Experience with BI and visualization tools such as Power BI, Tableau, or Looker.
  • Strong analytical thinking with the ability to translate complex data into actionable business insights.
  • Ability to work effectively in ambiguous, open-ended problem spaces.
  • Strong written and verbal communication skills with both technical and non-technical audiences.
  • Strong understanding of statistical concepts, predictive modeling techniques, machine learning workflows, model validation methodologies, and model performance evaluation.
  • Preferred Qualifications
  • Familiarity with Git or version control systems.
  • Background in financial services, portfolio analytics, forecasting, or operations analytics.
  • Strong background in predictive, descriptive, and prescriptive modeling techniques.
  • Understanding tree-based and survival models.

Core Competencies:

  • Drives Results
  • Decision Quality
  • Instills Trust
  • Balances Stakeholders
  • Collaborates
  • Resourcefulness
  • Nimble Learning
  • Plans and Aligns
  • Optimizes Work Processes
  • Tech Savvy

Benefits & conditions

Compensation: Compensation for this role is between $120,000 - $160,000 with bonus potential. This range does depend on various factors; for example education, experience, and location.

About the company

Invenio Financial, a Phillips & Cohen Associates company and leader in the debt purchasing and receivables management industry, is seeking a talented Data Scientist to join our growing Analytics team. This role will focus on performing deep dive analysis, develop machine learning, forecasting and prescriptive models. This role combines predictive modeling, financial modeling, data modeling, and applied analytics to build scalable processes to support portfolio acquisitions and strategy.

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