Senior Data Scientist - Applied Machine Learning

RESPONSIBILITIES:
Kforce as a client in San Jose, CA that is seeking a hands-on Senior Machine Learning Engineer/Data Scientist to join a small technical project team developing an ML solution focused on identifying and prioritizing high-value learning engagement opportunities. This role is ideal for a builder with deep experience in traditional machine learning, statistical modeling, feature engineering, and sales-oriented predictive analytics.

Key Responsibilities:
* Analyze complex, high-dimensional datasets to identify meaningful predictive signals
* Develop and evaluate classification, probability-based, and statistical models
* Perform feature engineering, feature selection, importance analysis, and experimentation across multiple data sources
* Build repeatable ML training, evaluation, and feature-engineering workflows
* Connect model performance to actionable sales, revenue, customer adoption, and opportunity outcomes
* Collaborate with technical and business stakeholders in an iterative development environment

REQUIREMENTS:
* Machine Learning: Deep hands-on experience with traditional predictive ML and statistical modeling, including classification, probability modeling, model evaluation/calibration, class imbalance, seasonality, temporal validation, and data leakage prevention
* Feature Engineering: Strong expertise in feature engineering, feature selection, feature importance, and determining which signals within complex, high-dimensional datasets provide meaningful predictive value
* Sales-Domain ML: Demonstrated experience applying machine learning and feature engineering within a sales, revenue, opportunity, or customer-focused domain; Experience connecting model outputs to actionable business outcomes is essential
* ML Techniques & Frameworks: Experience with Logistic Regression, Gradient Boosted Trees such as XGBoost/LightGBM, and Scikit-learn or comparable ML frameworks
* Python & Data: Advanced Python and SQL skills, including Pandas, NumPy, relational/database analysis, and experience working with structured and unstructured data
* ML Lifecycle: Experience developing ML training/evaluation workflows, feature-engineering pipelines, experiment tracking, model versioning/monitoring, and production-oriented ML practices
* Hands-On Development: Strong coding and analytical skills with the ability to independently explore data, build and test models, evaluate results, and iterate as data and business requirements evolve
* Important: This role requires deep applied machine learning expertise; GenAI/LLM experience can be complementary, but the primary focus is traditional ML, statistical modeling, feature engineering, and sales-oriented predictive analytics
* Experience with model evaluation/calibration, class imbalance, temporal validation, seasonality, and leakage prevention
* Experience with ML training/evaluation pipelines, experiment tracking, model monitoring, and versioning
* Ability to work with structured and unstructured enterprise data

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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