Data Scientist: Build Analytics-Driven ML & Dashboards

InnovitUSA; Boise (ID); On-site; USD 90,000 - 130,000; Full time

Job summary

InnovitUSA is seeking a Data Scientist to collect, clean, analyze, and interpret large datasets. The role requires knowledge of Python, SQL, statistics, ML, and data visualization to develop data-driven solutions.

Responsibilities include EDA, developing ML models, writing SQL queries, and building dashboards with Power BI, Tableau, or Python libraries. Collaboration with business teams and data engineers is essential.

Qualifications

• Proficient in Python for data analysis and modeling.
• Strong SQL knowledge to query databases.
• Solid foundation in statistics and probability.
• Experience with machine learning and model evaluation.
• Experience cleaning and preprocessing data from diverse sources.
• Ability to build visualizations and dashboards.
• Familiarity with Pandas/NumPy/Matplotlib/Seaborn.
• Experience with Scikit-learn algorithms.

Responsibilities

• Collect, clean, and preprocess structured and unstructured data.
• Perform exploratory data analysis to identify patterns and trends.
• Develop and implement machine learning models.
• Use statistical techniques to analyze business problems.
• Write SQL queries to extract and manipulate data from databases.
• Build dashboards and visualizations using Power BI, Tableau, or Python libraries.
• Evaluate model performance and improve accuracy.
• Collaborate with business teams, data engineers, and analysts.
• Communicate findings through reports and presentations.

Skills

Python programming

SQL and database concepts

Statistics and probability

Machine Learning

Data cleaning and preprocessing

Data visualization

Pandas

NumPy

Matplotlib

Seaborn

Scikit-learn

Problem-solving and analytical skills

Tools

Power BI

Tableau

Job description

InnovitUSA is seeking a Data Scientist to collect, clean, analyze, and interpret large datasets. The role requires knowledge of Python, SQL, statistics, ML, and data visualization to develop data-driven solutions.

Responsibilities include EDA, developing ML models, writing SQL queries, and building dashboards with Power BI, Tableau, or Python libraries. Collaboration with business teams and data engineers is essential.