8 Data Modeling jobs in Bahrain

• Assist in collecting and organizing data from various sources.
• Perform data cleaning and preprocessing tasks.
• Conduct exploratory data analysis to identify trends and patterns.
• Support the creation of reports, dashboards, and data visualizations.
• Help in interpreting data and generating insights for business stakeholders.
• Learn and apply various data analysis techniques and tools.
• Contribute to data quality assurance efforts.
• Participate in team meetings and present findings.
• Collaborate with senior analysts on ongoing projects.
• Develop foundational skills in statistical analysis and data modeling.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong analytical and quantitative skills.
• Proficiency in Microsoft Excel; knowledge of SQL is a plus.
• Familiarity with programming languages like Python or R is advantageous.
• Excellent problem-solving abilities and attention to detail.
• Good communication and interpersonal skills.
• Eagerness to learn and develop new skills in data analysis.
• Ability to work effectively in a team.

• Assist in collecting, cleaning, and organizing large datasets from various sources.
• Perform data analysis using statistical methods and tools.
• Develop reports and dashboards to visualize data insights.
• Identify trends, patterns, and anomalies within datasets.
• Support senior analysts in building predictive models.
• Collaborate with cross-functional teams to understand data needs.
• Ensure data accuracy and integrity throughout the analysis process.
• Learn and apply various data analysis software and techniques.
• Assist in documenting data processes and methodologies.
• Present findings and recommendations to stakeholders.

• Recent graduate with a degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong analytical and problem-solving skills.
• Proficiency in data analysis tools (e.g., Excel, SQL, Python/R basics).
• Excellent attention to detail and accuracy.
• Good written and verbal communication skills.
• Ability to work collaboratively in a team environment.
• A strong desire to learn and develop expertise in data analysis.

• Lead the statistical analysis and interpretation of complex research data.
• Develop and implement advanced data mining and machine learning models.
• Design experiments to optimize data collection and analysis.
• Manage and curate large scientific datasets.
• Create compelling data visualizations to communicate findings.
• Collaborate with research teams to define analytical needs and provide insights.
• Write clear and concise reports on research findings.
• Stay abreast of the latest advancements in data science and statistical methodologies.
• Mentor junior data analysts and researchers.
• Contribute to the publication of research findings in peer-reviewed journals.

• Ph.D. in Statistics, Computer Science, Physics, Mathematics, or a related quantitative field.
• Minimum of 6 years of experience in data analysis and scientific research.
• Proven expertise in statistical modeling, machine learning, and data mining.
• Proficiency in programming languages such as Python or R, including relevant libraries (e.g., NumPy, Pandas, Scikit-learn).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Strong understanding of experimental design and scientific research principles.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex concepts to diverse audiences.
• Experience in materials science or a related scientific discipline is a plus.

• Analyze satellite and aerial imagery (e.g., hyperspectral, multispectral, thermal) for mineral prospectivity mapping.
• Process and interpret LiDAR data for topographic and geological feature extraction.
• Develop and apply advanced algorithms for geological feature detection and classification using remote sensing data.
• Integrate remote sensing data with other geological datasets (e.g., geophysical, geochemical, drilling logs) for comprehensive analysis.
• Perform 3D geological modeling based on integrated datasets.
• Generate detailed technical reports, maps, and presentations on geological findings and mineral potential.
• Collaborate with geologists and data scientists globally via virtual communication platforms.
• Conduct literature reviews and research to stay current with advancements in geological remote sensing and data analysis techniques.
• Mentor junior geologists in the application of remote sensing tools and data interpretation.
• Ensure data quality, integrity, and proper archival of all analyzed information.

• Master's degree or Ph.D. in Geology, Earth Science, or a related field with a specialization in remote sensing or geoinformatics.
• Minimum of 5-7 years of experience in geological data analysis, with a strong focus on remote sensing applications in mining or exploration.
• Proficiency in remote sensing software (e.g., ENVI, ERDAS Imagine) and GIS platforms (e.g., ArcGIS, QGIS).
• Experience with programming languages commonly used in data science and GIS (e.g., Python, R) is highly advantageous.
• Demonstrated experience in mineral exploration, geological mapping, and resource estimation.
• Excellent understanding of geological principles and their application to mineral systems.
• Strong analytical and problem-solving skills with meticulous attention to detail.
• Exceptional written and verbal communication skills, with the ability to articulate complex technical information.
• Proven ability to work independently, manage time effectively, and meet project deadlines in a remote setting.
• Comfortable with virtual collaboration tools and workflows.

Join to apply for the Data Architect (Trading) role at Keyrock

Join to apply for the Data Architect (Trading) role at Keyrock

About Keyrock

Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation.

Data Architect

About Keyrock

Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation.

Today, we rock with over 180 team members around the world. Our diverse team hails from 42 nationalities, with backgrounds ranging from DeFi natives to PhDs. Predominantly remote, we have hubs in London, Brussels, Singapore and Paris, and host regular online and offline hangouts to keep the crew tight.

We are trading on more than 80 exchanges, and working with a wide array of asset issuers. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks.

But we’re more than a service provider. We’re an initiator. We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. We upgrade ecosystems by injecting liquidity into promising DeFi, RWA, and NFT protocols. And we push the industry's progress with our research and governance initiatives.

At Keyrock, we're not just envisioning the future of digital assets. We're actively building it.

Position Overview

The Data Architect is responsible for designing, implementing, and maintaining an organization's data architecture and strategy, ensuring that data is collected, stored, and processed efficiently and securely to support business intelligence, data analytics, and machine learning operations (MLOps) practices.

Key Responsibilities

• Designing Data Architecture: Plan and implement a robust, scalable data architecture that integrates data from various sources and supports diverse analytical needs, while optimizing costs and meeting business requirements.
• Implementing Data Engineering Pipelines: Design and develop data pipelines for data extraction, transformation, and loading (ETL) processes, ensuring data quality and consistency.
• Enabling Data Intelligence and Analytics: Build and maintain data warehouses, data marts, and data lakes to support business intelligence and data analytics initiatives.
• Supporting MLOps Practices: Collaborate with data scientists and machine learning engineers to design and implement data infrastructure and processes that support machine learning model development, deployment, and maintenance.
• Ensuring Data Security and Compliance: Implement security measures, policies, and procedures to safeguard data privacy and comply with relevant regulations.
• Data Governance and Management: Establish and enforce data governance policies and standards to ensure data quality, integrity, and accessibility.
• Collaborating with Cross-Functional Teams: Work closely with data engineers, data scientists, business analysts, and other stakeholders to understand data requirements and translate them into technical solutions.
• Staying Abreast of Technological Advancements: Keep up-to-date with emerging technologies and trends in data architecture, data engineering, and MLOps to identify opportunities for improvement and innovation.
• Optimizing Data Performance: Monitor and analyze data processing performance, identify bottlenecks, and implement optimizations to enhance efficiency and scalability.
• Documentation and Knowledge Sharing: Create and maintain comprehensive documentation of data architecture, models, and processing workflows.
  
  

• Extensive experience in data architecture design and implementation.
• Strong knowledge of data engineering principles and practices.
• Expertise in data warehousing, data modelling, and data integration.
• Experience in MLOps and machine learning pipelines.
• Proficiency in SQL and data manipulation languages.
• Experience with big data platforms (including Apache Arrow, Apache Spark, Apache Iceberg, and Clickhouse) and cloud-based infrastructure on AWS.
  
  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Preferred certifications (optional):
• AWS Cloud Data Engineer
• AWS Machine Learning Ops Engineer
  

• Passion for building scalable, reliable, and secure systems in a fast-paced environment.
• Ability to translate complex technical concepts into clear, actionable insights for technical teams.
• Strong interpersonal skills with the ability to work effectively across cross-functional teams.
• Excellent problem-solving and analytical skills.
  
  

• Competitive salary package
• Autonomy in your time management thanks to flexible working hours and the opportunity to work remotely
• The freedom to create your own entrepreneurial experience by being part of a team of people in search of excellence
  
  

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology

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