Data Scientist

Brooksource; Lansing (MI); On-site; USD 90,000 - 130,000; Full time

Job summary

Brooksource in Lansing, MI is seeking a hands-on machine learning engineer to develop and evaluate models using Python, and to build solutions for document classification, segmentation, and information extraction.

You will clean, parse, explore, and model real-world data; perform model evaluation and error analysis; document methodologies and results; and clearly communicate findings to both technical and non-technical stakeholders while moving models toward repeatable production workflows.

Qualifications

• 2–5 years of hands-on ML experience with Python.
• Experience with data preparation, modeling, evaluation, and error analysis.
• Strong analytical and problem-solving skills.
• Ability to assess model performance and communicate limitations.
• Strong written and verbal communication skills.
• Ability to work independently and collaboratively in ambiguous environments.

Responsibilities

• Develop and evaluate ML models using Python.
• Clean, parse, explore, and model messy real-world data.
• Build solutions for document classification, segmentation, and information extraction.
• Perform model evaluation and error analysis to identify strengths and weaknesses.
• Document methodologies, assumptions, experiments, and results.
• Clearly communicate technical findings to both technical and non-technical stakeholders.
• Work independently on ambiguous modeling problems and collaborate with technical partners.
• Help move successful models toward repeatable production workflows.

Skills

Machine Learning

Python

Data analysis

Communication skills

Job description

Responsibilities

• Develop and evaluate machine learning models using Python.
• Clean, parse, explore, and model messy real-world data.
• Build solutions for document classification, segmentation, and information extraction.
• Perform model evaluation and error analysis to identify strengths, weaknesses, and limitations.
• Document methodologies, assumptions, experiments, and results.
• Clearly communicate technical findings to both technical and non-technical stakeholders.
• Work independently on ambiguous modeling problems and collaborate with technical partners.
• Help move successful models toward repeatable production workflows.

Required Qualifications

• 2–5 years of hands‑on machine learning experience using Python.
• Experience with data preparation, modeling, evaluation, and error analysis.
• Strong analytical and problem‑solving skills.
• Ability to assess model performance and communicate limitations and appropriate use.
• Strong written and verbal communication skills.
• Ability to work independently and collaboratively in an ambiguous environment.

Preferred Qualifications

• Experience with Document Intelligence, including document segmentation, classification, information extraction, OCR, or document understanding.
• NLP experience with text classification, entity extraction, embeddings, transformers, or LLMs.
• Experience evaluating probabilistic or LLM-based systems.
• Experience moving ML models from experimentation into production.

Direct Document Intelligence experience is strongly preferred, but candidates with strong machine learning and meaningful NLP/text modeling experience may also be a good fit.

EEO Statement:

Brooksource is an equal opportunity employer that does not discriminate on the

basis of actual or perceived race, color, creed, religion, national origin, ancestry,

citizenship status, age, sex or gender (including pregnancy, childbirth, lactation

and related medical conditions), gender identity or gender expression, sexual

orientation, marital status, military service and veteran status, physical or mental

disability, protected medical condition as defined by applicable state or local law,

genetic information, or any other characteristic protected by applicable federal,

state, or local laws and ordinances.

Pay Disclaimer:

The pay range for this job level is a general guideline only and not a guarantee of

compensation or salary. Additional factors considered in extending an offer

include (but are not limited to) responsibilities of the job, education, experience,

knowledge, skills, and abilities, as well as internal equity, alignment with market

data, applicable bargaining agreement (if any), or other law.