Data Scientist

Simarn Solutions; San Antonio (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Simarn Solutions in San Antonio, TX seeks an experienced Data Scientist with hands-on expertise in Machine Learning, Feature Engineering, Statistical Modeling, Python, SQL, and NLP to build predictive models and productionize analytics.

You will collaborate with Data Engineering and MLOps teams on deployment, monitoring, and continuous improvement, while translating business needs into data-driven insights.

Qualifications

• 8+ years of experience in Data Science, Analytics, or Machine Learning.
• Strong hands-on experience with Feature Selection & Feature Engineering.
• Strong knowledge of Statistics, Hypothesis Testing, Regression Analysis, PCA & Predictive Modeling.
• Advanced SQL and large-scale data analysis.
• Experience with NLP, text processing & feature extraction.
• Experience with ETL/ELT, Data Pipelines & Data Engineering concepts.
• Understanding of model deployment and MLOps.
• Strong analytical, problem-solving, documentation, and stakeholder communication skills.

Responsibilities

• Perform advanced feature selection and feature engineering using various techniques.
• Conduct exploratory data analysis (EDA), statistical validation, and data profiling.
• Build, train, validate, tune, and optimize Machine Learning and predictive models.
• Develop scalable feature-engineering frameworks for structured and unstructured datasets.
• Use Python and SQL for large-scale data extraction, transformation, analysis, and validation.
• Apply NLP and text-processing techniques for feature extraction and predictive modeling.
• Build and optimize ETL/ELT pipelines, data transformations, and feature datasets.
• Partner with Data Engineering and MLOps teams on model deployment, monitoring, performance tracking, and continuous improvement.
• Document feature-selection methodologies, statistical findings, model development processes, pipeline logic, and deployment requirements.
• Collaborate with business and product stakeholders to translate business requirements into analytical solutions and actionable insights.

Skills

Data Science

Machine Learning

Feature Engineering

Statistical Modeling

Python

SQL

NLP

EDA

MLOps

Model Deployment

Tools

Python

SQL

NLP

Job description

We are looking for an experienced Data Scientist with strong hands-on expertise in Machine Learning, Feature Engineering, Statistical Modeling, Python, SQL, and NLP. The ideal candidate will have experience building predictive models, identifying high-value features, working with large datasets, and collaborating with Data Engineering/MLOps teams to productionize analytical solutions.

Key Responsibilities

• Perform advanced feature selection and feature engineering using correlation analysis, hypothesis testing, regression analysis, Information Value (IV), Weight of Evidence (WoE), PCA, and feature-importance techniques.
• Conduct exploratory data analysis (EDA), statistical validation, and data profiling to identify meaningful patterns and predictive variables.
• Build, train, validate, tune, and optimize Machine Learning and predictive models.
• Develop scalable feature-engineering frameworks for structured and unstructured datasets.
• Use Python and SQL for large-scale data extraction, transformation, analysis, and validation.
• Apply NLP and text-processing techniques for feature extraction and predictive modeling.
• Build and optimize ETL/ELT pipelines, data transformations, and feature datasets in collaboration with Data Engineering teams.
• Partner with Data Engineering and MLOps teams on model deployment, monitoring, performance tracking, and continuous improvement.
• Document feature-selection methodologies, statistical findings, model development processes, pipeline logic, and deployment requirements.
• Collaborate with business and product stakeholders to translate business requirements into analytical solutions and actionable insights.

Required Skills

• 8+ years of experience in Data Science, Analytics, or Machine Learning
• Strong hands-on experience with Feature Selection & Feature Engineering
• Strong knowledge of Statistics, Hypothesis Testing, Regression Analysis, PCA & Predictive Modeling
• Advanced SQL and large-scale data analysis
• Experience with NLP, text processing & feature extraction
• Experience with ETL/ELT, Data Pipelines & Data Engineering concepts
• Understanding of model deployment and MLOps
• Strong analytical, problem-solving, documentation, and stakeholder communication skills

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