Senior Data Science Engineer 8490 R
Summary
Senior Data Scientist on a large-scale consumer platform team: analyze massive datasets, build ML models (prediction, anomaly detection, pattern recognition), design experiments and metrics, and partner with Product and Engineering to drive product decisions. Core stack: Python, SQL, Spark/Hadoop/Hive, TensorFlow/PyTorch/scikit-learn, BigQuery.
Join Akvelon — build products used by millions!
Akvelon is an IT company with 20+ years of experience and 1,200+ engineers across 15+ locations worldwide.
We work with both well-known global tech companies, including Microsoft, Facebook, Airbnb, Dropbox, and Pinterest, and with growing startups.
Our teams are involved in different types of engineering projects, from cloud solutions and AI/ML systems to big data, web, and mobile applications.
Since we are remote-first, our engineers work in distributed teams with flexible hours. We value ownership, clear communication, and the ability to take responsibility for your part of the work.
About the project
The client is a global platform that connects millions of people through communities and content, driving large-scale, data-driven consumer experiences. As a Senior Data Scientist, you’ll join a highly collaborative team using advanced analytics, experimentation, and machine learning to improve product experiences, uncover strategic insights, and drive growth. You’ll work closely with Product, Engineering, ML, and Data Science teams, turning large-scale datasets into actionable insights and solutions that directly influence product decisions and user engagement.
Requirements
- 5+ years of experience in Data Science, Machine Learning, or a related field
- Advanced SQL and strong Python skills
- Strong experience working with Big Data and large-scale datasets
- Solid knowledge of statistical modeling, machine learning, experimental design, and causal inference
- Experience with large-scale data processing tools such as Spark, Hadoop, or Hive
- Experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch
- Strong product sense and ability to translate product and business questions into data-driven solutions
- Strong communication skills and experience collaborating with Product, Engineering, and Data Science teams
- Ability to independently investigate complex problems and communicate actionable insights
- Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, or a related field
- Experience in consumer technology or consumer-facing products
- Experience with causal inference and A/B testing
- Experience with BigQuery
- Experience building ML models for prediction, anomaly detection, or pattern recognition
- Experience building dashboards and self-service data assets
Responsibilities
- Develop and apply data science solutions to support consumer product teams
- Analyze large-scale datasets to identify trends, patterns, and opportunities
- Design metrics, experiments, and analytical frameworks to measure product impact
- Build ML models and statistical methods for prediction, anomaly detection, and pattern recognition
- Create data assets, dashboards, and reporting tools that enable teams to make data-driven decisions
- Partner with Product and Engineering teams to define problems and translate them into effective data solutions
- Uncover strategic insights and communicate recommendations that influence product direction
- Present findings clearly to technical and non-technical stakeholders and drive alignment on data-informed decisions
- Preferable overlap with PST working hours to support collaboration with the client and cross-functional teams