What are the responsibilities and job description for the Data Scientist - W2 position at Medinext Global LLC?
Data Scientist - W2
Job Overview
Medinext Global LLC is seeking a talented and analytical Data Scientist with 1-3 years of professional experience to join our team. The ideal candidate will have hands-on experience with Python, SQL, statistical analysis, machine learning, and data visualization.
The Data Scientist will work with business and technical teams to analyze complex datasets, develop predictive models, identify meaningful patterns, and deliver data-driven insights that support business decisions.
Responsibilities
Collect, clean, transform, and analyze structured and unstructured datasets.
Develop statistical and machine learning models to solve business problems.
Perform exploratory data analysis and identify trends, patterns, and relationships.
Build and evaluate predictive models using appropriate machine learning techniques.
Develop data visualizations, dashboards, and reports to communicate findings.
Write efficient SQL queries to extract and analyze data from databases.
Use Python for data analysis, modeling, and automation.
Collaborate with data engineers, software engineers, product teams, and business stakeholders.
Evaluate model performance and improve models based on business requirements.
Present technical findings and recommendations to both technical and non-technical audiences.
Document analytical approaches, models, methodologies, and results.
Stay current with emerging data science, machine learning, and AI technologies.
Required Qualifications
1–3 years of professional experience in Data Science, Machine Learning, or a related field.
Strong proficiency in Python.
Strong knowledge of SQL and relational databases.
Experience with Pandas, NumPy, Scikit-learn, or similar data science libraries.
Understanding of statistics, probability, and machine learning concepts.
Experience with data cleaning, preprocessing, feature engineering, and exploratory data analysis.
Experience building and evaluating machine learning models.
Familiarity with data visualization tools such as Matplotlib, Seaborn, Power BI, or Tableau.
Strong analytical and problem-solving skills.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field preferred.
Preferred Qualifications
Experience with TensorFlow or PyTorch.
Knowledge of deep learning and neural networks.
Experience with AWS, Azure, or Google Cloud.
Familiarity with Databricks, Spark, or other big-data technologies.
Experience with NLP or Generative AI is a plus.
Knowledge of MLOps and model deployment practices.
Experience with Git and CI/CD.
Familiarity with Agile/Scrum methodologies.
Employment Type
W2 - Full Time
Experience
1-3 Years