Sr. Data Scientist

Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, or a related field.

7+ years of experience in Data Science, Machine Learning, or a related field.

Experience working with consumer-facing products and large-scale data.

Advanced SQL and strong Python skills are a must.

Strong understanding of statistical modeling, machine learning algorithms, causal inference, and experimental design.

Experience with large-scale data processing and analysis using technologies such as Spark, Hadoop, or Hive; BigQuery is a plus.

Experience with SQL and relational databases.

Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.

Exceptional product sense and the ability to translate product/business problems into data science solutions.

Strong communication skills and experience working with cross-functional stakeholders.

Design, develop, and apply Data Science solutions to improve consumer-facing products.

Analyze large-scale datasets to identify trends, patterns, opportunities, and areas for improvement.

Develop and maintain data assets, including analytical tables, datasets, and self-service dashboards.

Build reporting and monitoring dashboards to help Product and Engineering teams understand key metrics and investigate changes.

Define and evaluate product metrics and measurement frameworks.

Design, analyze, and interpret experiments, including A/B tests.

Apply statistical modeling, causal inference, and machine learning methods to product problems.

Develop ML and DS solutions for use cases such as anomaly detection, prediction, and pattern recognition.

Partner with Product Managers and Engineers to translate product requirements and business questions into data science solutions.

Identify strategic insights and communicate them clearly to stakeholders.

Present analytical findings, experiment results, and recommendations to both technical and non-technical audiences.

Contribute to data-driven product strategy and decision-making.

Experience working in the Consumer Technology space.

Hands-on experience with causal inference and A/B testing.

Flexible working schedule: 8 hours per day, 40 hours per week withing Eastern Time (ET)

Paid vacation, sick leave (without a sickness list)

Official state holidays – 11 days considered public holidays

Professional growth while attending challenging projects and the possibility to switch your role, master new technologies and skills with company support

Personal Career Development Plan (CDP)

Employee support program (Discount, Care, Health, Legal compensation)

Paid external training, conferences, and professional certification that meet the company’s business goals

Internal workshops & seminars

Corporate library (Paper/E-books) and internal English classes.