Principal Data Scientist

About the Position

Akvelon is an American company with offices in Seattle, Mexico, Ukraine, Poland, and Serbia. Our company is an official vendor of Microsoft and Google. Our clients also include Amazon, Evernote, Intel, HP, Reddit, Pinterest, AT&T, T-Mobile, Starbucks, and LinkedIn. To work with Akvelon means to be connected with the best and brightest engineering teams from around the globe and working with an actual technology stack building Enterprise, CRM, LOB, Cloud, AI and Machine Learning, Cross-Platform, Mobile, and other types of applications customized to client’s needs and processes.

We stand with Ukraine!

About the Role

As a Principal 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.

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.

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.

Nice to Have

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

We Offer

• Flexible working schedule: 8 hours per day, 40 hours per week within 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.

About the Company

Please note: This position is open only to candidates based in LATAM and is not open to U.S.-based applicants.

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