About the Role
Simulmedia is a trailblazer in the world of data-driven advertising, known for its innovative approach to optimizing ad placements and campaign effectiveness through analytics and machine learning. Our mission is to revolutionize the advertising sector by enabling brands to reach their audiences more effectively.
We are seeking a motivated Middle Data Scientist to join our data science team. The ideal candidate has solid experience with supervised machine learning, strong analytical skills, and is comfortable working with real-world, large-scale data. In this role, you will contribute to building, improving, and maintaining machine learning models that support our advertising products and business decisions.
This position is based in Ukraine. The team primarily works remotely, with occasional in-person meetings in the Kyiv or Lviv office.
Key Responsibilities
- Develop and maintain supervised machine learning models to support ad targeting, measurement, and campaign optimization.
- Perform data analysis, data validation, and feature engineering on large and complex datasets.
- Collaborate with product, engineering, and analytics teams to translate business needs into data science solutions.
- Evaluate model performance using appropriate metrics and iterate on model improvements.
- Support optimization and experimentation efforts related to advertising performance.
- Assist with deploying models to production in collaboration with engineering teams.
- Monitor model performance and help troubleshoot issues in production.
- Communicate results, insights, and limitations to both technical and non-technical stakeholders.
- Stay up to date with industry best practices in data science and machine learning.
Qualifications
Education:
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
Experience:
- 2–4 years of experience in data science, machine learning, or a related analytical role.
- Hands-on experience applying machine learning to real business problems.
Technical Skills:
- Proficiency in Python.
- Solid experience with SQL and relational databases.
- Experience with machine learning libraries such as scikit-learn. Experience with TensorFlow or PyTorch is a plus.
- Good understanding of supervised learning techniques such as linear regression, logistic regression, and tree-based models including decision trees, random forests, and gradient boosting.
- Experience with data manipulation and analysis using pandas and NumPy.
- Familiarity with model evaluation techniques and performance metrics.
- Basic understanding of working with production systems or machine learning pipelines is a plus.
Other Skills:
- Strong analytical and problem-solving abilities.
- Ability to work independently while collaborating within a team.
- Clear communication skills and ability to explain technical concepts simply.
- Strong organizational skills and attention to detail.
- Comfortable communicating with U.S.-based teams.