Data Scientist

Machine Learning Technologies, LLC; Bentonville (AR); On-site; USD 110,000 - 150,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking an experienced Data Scientist to collect, analyze, and interpret large datasets to identify business insights and support data-driven decision-making.

The role requires strong Python, SQL, machine learning, statistics, and data visualization skills, with hands-on work building, evaluating, and deploying predictive models. You will collaborate with data engineers and stakeholders to create dashboards and monitor model performance in production.

Qualifications

• Experience collecting, cleaning, preprocessing, and analyzing structured and unstructured datasets.
• Ability to develop and implement machine learning models to solve business problems.
• Experience performing exploratory data analysis to identify trends and relationships.
• Proficiency in building predictive models using supervised and unsupervised learning.
• Strong background in developing statistical models and algorithms to improve performance.
• Proficient with Python libraries such as Pandas, NumPy, Scikit-learn, SciPy.
• Ability to write complex SQL queries to extract, transform, and analyze data.
• Experience creating data visualizations and dashboards (Power BI, Tableau, or Matplotlib).
• Knowledge of feature engineering and model evaluation metrics; RMSE, F1, etc.
• Experience deploying models into production and monitoring performance.

Responsibilities

• Collect, clean, preprocess, and analyze structured and unstructured datasets.
• Develop and implement machine learning models to solve business problems.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and relationships.
• Build predictive models using supervised and unsupervised learning techniques.
• Develop statistical models and algorithms to improve business performance.
• Use Python libraries such as Pandas, NumPy, Scikit-learn, and SciPy for data analysis.
• Write complex SQL queries to extract, transform, and analyze data from databases.
• Develop data visualizations and dashboards using Power BI, Tableau, or Matplotlib.
• Apply feature engineering and feature selection techniques to improve model accuracy.
• Evaluate machine learning models using performance metrics such as accuracy, precision, recall, F1-score, and RMSE.
• Work with large datasets using Spark, Hadoop, or cloud-based data platforms.
• Collaborate with data engineers, business analysts, and stakeholders to understand business requirements.
• Deploy machine learning models into production environments.
• Monitor model performance and perform model tuning and optimization.
• Document data science processes, findings, and recommendations.

Skills

Python

SQL

Machine learning

Statistical analysis

Data visualization

Predictive modeling

Tools

Pandas

NumPy

Scikit-learn

SciPy

Job description

We are looking for an experienced Data Scientist responsible for collecting, analyzing, and interpreting large datasets to identify business insights and support data-driven decision-making. The candidate should have strong experience in Python, SQL, machine learning, statistical analysis, data visualization, and predictive modeling.

Roles and Responsibilities:

• Collect, clean, preprocess, and analyze structured and unstructured datasets.
• Develop and implement machine learning models to solve business problems.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and relationships.
• Build predictive models using supervised and unsupervised learning techniques.
• Develop statistical models and algorithms to improve business performance.
• Use Python libraries such as Pandas, NumPy, Scikit-learn, and SciPy for data analysis.
• Write complex SQL queries to extract, transform, and analyze data from databases.
• Develop data visualizations and dashboards using Power BI, Tableau, or Matplotlib.
• Apply feature engineering and feature selection techniques to improve model accuracy.
• Evaluate machine learning models using performance metrics such as accuracy, precision, recall, F1-score, and RMSE.
• Work with large datasets using Spark, Hadoop, or cloud-based data platforms.
• Collaborate with data engineers, business analysts, and stakeholders to understand business requirements.
• Deploy machine learning models into production environments.
• Monitor model performance and perform model tuning and optimization.
• Document data science processes, findings, and recommendations.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.