Senior-level Machine Learning Engineer / Data Scientist

BCforward

Plano (TX)

Hybrid

USD 130,000 - 176,000

Full time

14 days+

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Job summary

BCforward seeks a Senior-level Machine Learning Engineer / Data Scientist in Plano, TX for a contract role (11 months, potential for contract-to-hire). You will develop Python-based ML models, perform feature engineering, and deploy scalable classification solutions from data exploration to production.

Hybrid onsite schedule with collaboration across teams. The ideal candidate has 5–10 years of hands-on data science experience, strong Python with pandas/NumPy/scikit-learn/XGBoost, and a track

Qualifications

  • Master's or PhD in computer science, statistics, mathematics, engineering, data science, or related field.
  • 5–10 years hands-on data science or ML engineering experience in technical environments.
  • Strong Python development with common ML libraries.
  • Experience with large structured datasets and feature engineering.
  • Ability to evaluate models using standard metrics and error analysis.
  • Experience packaging and deploying models in production environments.

Responsibilities

  • Design, train, validate, and tune supervised ML classification models.
  • Perform data exploration, cleansing, and feature engineering for model inputs.
  • Develop Python-based workflows and pipelines for data prep and model training.
  • Evaluate model performance using precision, recall, F1, ROC-AUC, and confusion matrices.
  • Package and deploy models into production or near-production environments.
  • Create technical documentation for data assumptions, features, and validation results.
  • Collaborate with engineers, analysts, and stakeholders to ensure maintainability and measurable outcomes.

Skills

Python development
Pandas
NumPy
scikit-learn
XGBoost
ML engineering
Model evaluation
Feature engineering
Data exploration
Agile delivery
Documentation
AI tooling

Education

Master's or PhD in CS/stats/math/engineering/data science

Tools

pandas
NumPy
scikit-learn
XGBoost

Job description

About BCforward

BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity.

Job Title

Job Title: Senior-level Machine Learning Engineer / Data Scientist

Location

Location: Plano, TX

Duration

Duration: Contract - 11 months (potential contract-to-hire)

Pay Range

Pay Range: $73.67/hr (W2)

Job ID

Job ID: 410471

Job Description

We are seeking a Senior-level Machine Learning Engineer / Data Scientist to join our dynamic team. The ideal candidate will have strong experience in Python-based model development, feature engineering, evaluation, and deployment and a proven ability to deliver scalable classification models from data exploration through production implementation.

Responsibilities
  • Design, build, train, validate, and tune supervised machine learning classification models using structured, behavioral, and transactional data.
  • Perform hands‑on data exploration, cleansing, transformation, and feature engineering to create reliable inputs for model development.
  • Develop repeatable Python-based workflows, scripts, and pipelines for dataset preparation, model training, evaluation, and scoring.
  • Evaluate classification performance using precision, recall, F1 score, ROC‑AUC, and confusion matrices, and iterate based on false positive and false negative analysis.
  • Package and deploy models into scalable production or near-production environments in partnership with engineering teams.
  • Troubleshoot data quality, pipeline, model performance, and integration issues across development, testing, and deployment phases.
  • Create clear technical documentation for data assumptions, feature logic, model design, validation results, implementation details, and operations.
  • Collaborate with engineers, analysts, and stakeholders to ensure solutions are maintainable, explainable, and aligned to measurable outcomes.
Required Skills & Qualifications
  • Master's or PhD in computer science, statistics, mathematics, engineering, data science, or a related discipline.
  • 5-10 years of hands‑on data science or machine learning engineering experience in technical environments.
  • Strong Python development with pandas, NumPy, scikit-learn, XGBoost, or similar libraries.
  • Deep understanding of supervised classification, feature engineering, model training, hyperparameter tuning, validation, threshold selection, and performance evaluation.
  • Experience with large structured datasets, data cleansing and transformation, exploratory analysis, and repeatable preparation workflows.
  • Ability to evaluate models using precision, recall, F1, ROC‑AUC, confusion matrices, and error analysis.
  • Experience packaging, versioning, testing, and integrating models or scoring logic into application workflows.
  • Strong technical communication and documentation skills.
  • Experience using generative AI tools such as Microsoft Copilot and applying prompt engineering techniques.
Preferred Skills
  • Classification models for fraud, risk, cybersecurity, authentication, customer behavior, or anomaly detection.
  • MLOps practices including version control, automated testing, CI/CD, monitoring, and reproducible deployments.
  • Real‑time or near real‑time inference design and integration with production decisioning workflows.
  • Distributed processing and cloud platforms such as Spark, Databricks, Hadoop, AWS, or Azure.
  • Working knowledge of SQL for data extraction, joins, profiling, and validation.
  • Dashboards, reporting, or visualizations for model performance and operational trends.
  • Explainable AI, model governance, responsible AI, bias evaluation, auditability, and risk controls.
  • Prior experience in Agile delivery environments.
Work Arrangement & Interview Process
  • Hybrid schedule with a minimum of 3 days onsite per week in Plano, TX.
  • Start month: October or November.
  • Interview process: 1-2 rounds. Video required. In-person required.
  • ID verification via Glider.
  • This role will require resources that do not require sponsorship now or in the future.
Submission Guidance

On resume, list current location, relocation plan, availability or start date, and cooling‑off status if applicable.

Why BCforward?
  • Competitive compensation and benefits.
  • Opportunities for growth with global clients.
  • Supportive, inclusive culture that values innovation and people.
  • Exposure to cutting‑edge technologies and projects.
About Our Commitment

BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status.

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