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Data Scientist cum Engineer
2 months ago
We are seeking a highly skilled Data Scientist cum Engineer to join our team at the Society of Exploration Geophysicists. As a key member of our organization, you will play a critical role in driving business growth and innovation through data-driven insights.
Key Responsibilities- Collaborate with Cross-Functional Teams: Work closely with Applied Researchers, Engineers, Analytics, and other multi-functional teams to design, develop, and deploy end-to-end production-ready solutions that meet business objectives.
- Design and Implement Data Pipelines: Develop efficient data pipelines to collect, process, and analyze large datasets, ensuring data quality and integrity.
- Integrate Machine Learning Models: Deploy machine learning models into production systems, leveraging expertise in data science and engineering to drive business outcomes.
- Conduct Data Analysis and Insights: Analyze complex datasets to identify trends, insights, and opportunities within the advertising domain, providing actionable recommendations to technical and non-technical stakeholders.
- Build Data Dashboards: Design and develop dashboards to monitor system and business performance, ensuring timely and accurate reporting.
- Education and Experience: Bachelor's or Master's degree in Computer Science or equivalent experience.
- Technical Skills: Proficiency in big data technologies (e.g., Spark, Hadoop) and database technologies (e.g., SQL, NoSQL), as well as strong programming skills in SQL, Python, Scala, or Java.
- Machine Learning Expertise: Good understanding of machine learning applications and experience in solving problems using data science and deploying models into production.
- Analytical and Communication Skills: Strong ability to analyze large datasets, identify trends, and derive actionable insights, with excellent communication skills to present findings to technical and non-technical stakeholders.
- Collaboration and Leadership: Ability to work effectively with multiple stakeholders, including Applied Researchers, Engineers, Analytics, team leaders, and other cross-functional teams.
