Data Scientist

Aone Consulting, LLC; Poland; On-site; PLN 133,920 - 178,560; Full time

Job summary

A data analytics firm based in Poland is seeking a Data Scientist responsible for collecting and interpreting large datasets to inform data-driven decisions. The role involves utilizing statistical methods and machine learning techniques, including data cleaning, exploratory analysis, and model development. The ideal candidate will have a degree in a relevant field and skills in Python, R, or SQL. This position offers an engaging environment where you work closely with business teams to translate analysis into practical insights.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science or related field.
• Strong understanding of Statistics & probability, Hypothesis testing, Experimental design (A/B testing).
• Experience with Python, R, or SQL programming.

Responsibilities

• Collect, analyze, and interpret large datasets for decision-making.
• Clean, structure, and preprocess raw data.
• Perform exploratory data analysis to find patterns and trends.
• Develop predictive models using regression, classification, and clustering.
• Deploy models into production environments and monitor performance.

Skills

Python

R

SQL

Statistics & probability

Data Analysis

Education

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science or related field

Tools

Spark

Hadoop

Job description

A Data Scientist will be responsible for collecting, analyzing, and interpreting large datasets to help organizations make data-driven decisions. They will use statistical methods, programming, and machine learning techniques to uncover insights and build predictive models.

Data Collection & Cleaning

• Gather data from databases, APIs, logs, or external sources
• Clean, structure, and preprocess raw data (handle missing values, outliers)

2. Data Analysis & Exploration

• Perform exploratory data analysis (EDA) to find patterns and trends
• Use statistical techniques to interpret data
• Develop predictive models using techniques like regression, classification, clustering
• Train, test, and tune machine learning models
• Create dashboards, charts, and reports (e.g., using tools like Tableau or Python libraries)
• Explain insights to non-technical stakeholders clearly

5. Deployment & Monitoring

• Deploy models into production environments
• Monitor performance and retrain models when needed
• Work with engineers, analysts, and business teams
• Translate business problems into data-driven solutions

Requirements

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science or related field

Technical Skills

• Programming: Python, R, or SQL
• Big data tools (optional but valuable): Spark, Hadoop
• Strong understanding of Statistics & probability, Hypothesis testing, Experimental design (A/B testing)