Sr. Data Scientist

Requirements:

• • 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.

Projects

As a Senior Data Scientist, you will combine strong technical expertise with a deep understanding of product and business problems. You will analyze large-scale datasets, design and evaluate experiments, develop data science solutions, and communicate insights to cross-functional stakeholders.

The role covers a broad range of areas including product analytics, experimentation, measurement, statistical modeling, and machine learning.

Key Responsibilities:

• 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.

Working conditions and benefits:

• 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.

Nice to Have:

• Experience working in the Consumer Technology space.
• Hands-on experience with causal inference and A/B testing.