confirmed product manager (b2b saas data & ai)

business analyst

backend developer

electrical engineer

3d designer

chief engineer

data engineer

GSSTech Group

<div><p>We are seeking a highly skilled Data Engineer with strong expertise in <b>PySpark</b> and the <b>Cloudera Data Platform (CDP)</b>. The ideal candidate will design, develop, and maintain scalable data pipelines while ensuring high data quality, performance, and availability across the organisation.</p><p>
This role requires hands-on experience in big data ecosystems, cloud-native technologies, and advanced data processing frameworks. You will collaborate with cross-functional teams to build reliable and high-performance data solutions that drive business insights.</p><p></p><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><h3 class="jobSectionHeader"><b>
1. Data Pipeline Development</b></h3><ul>
<li>Design, develop, and maintain scalable ETL/ELT pipelines using PySpark on CDP
</li><li>Ensure data integrity, reliability, and performance optimisation
</li></ul><h3 class="jobSectionHeader"><b>2. Data Ingestion</b></h3><ul>
<li>Develop ingestion frameworks to collect data from relational databases, APIs, streaming sources, and file systems
</li><li>Load structured and unstructured data into Data Lake/Data Warehouse environments
</li></ul><h3 class="jobSectionHeader"><b>3. Data Transformation &amp; Processing</b></h3><ul>
<li>Process, cleanse, and transform large-scale datasets using PySpark
</li><li>Build reusable data processing components
</li></ul><h3 class="jobSectionHeader"><b>4. Performance Optimisation</b></h3><ul>
<li>Tune Spark jobs and Cloudera components for optimal performance
</li><li>Optimise memory, partitioning, and execution plans
</li><li>Reduce ETL runtime and improve cluster efficiency
</li></ul><h3 class="jobSectionHeader"><b>5. Data Quality &amp; Validation</b></h3><ul>
<li>Implement data validation checks and monitoring mechanisms
</li><li>Ensure end-to-end data quality and governance standards
</li></ul><h3 class="jobSectionHeader"><b>6. Automation &amp; Orchestration</b></h3><ul>
<li>Automate workflows using tools such as Apache Oozie, Apache Airflow, or similar orchestration frameworks
</li><li>Maintain CI/CD integration for data pipelines
</li></ul><h3 class="jobSectionHeader"><b>7. Monitoring &amp; Support</b></h3><ul>
<li>Monitor pipeline health and troubleshoot failures
</li><li>Provide production support and continuous improvements
</li></ul><p></p><h3 class="jobSectionHeader"><b>Required Skills &amp; Qualifications</b></h3><ul>
<li>5+ years of experience in Data Engineering
</li><li>Strong hands-on experience in <b>PySpark</b>
</li><li>Experience working on <b>Cloudera Data Platform (CDP)</b>
</li><li>Strong knowledge of Hadoop ecosystem (HDFS, Hive, Impala, YARN)
</li><li>Proficiency in SQL and data modelling concepts
</li><li>Experience with workflow orchestration tools (Airflow, Oozie, etc.)
</li><li>Good understanding of data warehousing concepts
</li><li>Experience with performance tuning and optimisation
</li></ul><p></p><h3 class="jobSectionHeader"><b>Good to Have</b></h3><ul>
<li>Experience with cloud platforms (AWS, Azure, GCP)
</li><li>Knowledge of streaming tools (Kafka, Spark Streaming)
</li><li>Exposure to DevOps practices and CI/CD pipelines
</li><li>Banking/Financial Services domain experience</li></ul></div>

Data Engineer (PySpark)

Moreton Capital Partners

<div><h3 class="jobSectionHeader"><b>Data Engineer - Systematic Commodities Hedge Fund</b></h3><p>
Moreton Capital Partners is a systematic commodities hedge fund preparing to launch live trading across global futures markets. Our research and trading systems rely on robust, scalable data infrastructure. We are looking for Data Engineers to help us design, build, and optimize that infrastructure alongside senior engineers and the CIO.</p><p></p><p><b>
Key Responsibilities</b><br>
You&rsquo;ll work on projects such as:</p><ul>
<li>
Designing and maintaining data pipelines to collect, clean, and transform market and alternative datasets (e.g., futures, options, weather, satellite, fundamentals).</li>
<li>Building ETL workflows using Python (pandas/polars) and orchestration tools such as Airflow or Prefect.</li>
<li>Structuring data warehouses and APIs (SQL, Snowflake, or similar) for efficient query and analysis.</li>
<li>Developing data quality and monitoring systems for latency, completeness, and integrity.</li>
<li>Assisting in cloud deployments (AWS, Docker) and automation for data ingestion and versioning.</li>
<li>Collaborating with Quant Researchers to make research datasets reproducible and production-ready.</li>
<li>Contributing to internal documentation and code standards to ensure long-term maintainability.</li>
</ul><p><b>
Requirements</b></p><ul><li>
Strong programming skills in Python and familiarity with SQL.</li></ul><ul>
<li>Understanding of data structures, algorithms, and software engineering best practices.</li>
<li>Interest in large-scale data systems, cloud computing, or distributed processing.</li>
<li>Self-starter with curiosity and attention to detail.</li>
</ul><p></p><p>
Bonus points for:</p><br>
<ul>
<li>
Experience with Airflow, Docker, or AWS.</li>
<li>Familiarity with Snowflake, Polars, or Pandas workflows.</li>
<li>Exposure to financial or time-series data.</li>
<li>Understanding of CI/CD, version control, or testing frameworks.</li>
</ul><p><b>
Benefits</b></p><ul>
<li>
Real-world impact: Help build data systems that directly feed institutional-grade trading research and live execution.</li>
<li>Technical depth: Gain hands-on experience with distributed data pipelines, cloud infrastructure, and production data engineering.</li>
<li>Mentorship: Work closely with senior engineers, the CIO, and Quant Researchers on live projects.</li>
<li>Collaborative culture: Inclusive, high-trust team that values initiative and learning.</li>
<li>Compensation: Competitive stipend/salary based on experience.</li></ul></div>

Data Engineer - Systematic Commodities Hedge Fund

Parsons

<div>In a world of possibilities, pursue one with endless opportunities. Imagine Next!<br>
<p></p>
At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what&rsquo;s possible.<p></p><p><b><br>
Job Description:</b></p><div><p>
Position Overview</p></div><p>
Parsons is seeking a high-potential Data Engineer Graduate Intern to join our Technology and Innovation team. This role is designed for candidates with strong analytical foundations and an interest in building scalable, enterprise-grade data platforms that support operational, engineering, and executive decision-making.</p><p>
As an intern, you will contribute to the design, development, and optimization of cloud-based data pipelines and analytics platforms, primarily within the Microsoft Azure ecosystem. You will work alongside experienced data engineers, architects, and product teams on real delivery programs, gaining exposure to enterprise data standards, governance, and DevOps practices.</p><p><b>
Key Responsibilities</b></p><p><b>
Data Processing</b></p><ul><li>
Work with frameworks like Apache Spark, Hadoop, or Apache Beam to process large datasets efficiently.</li><li>
Support development of batch and streaming data pipelines using Python and distributed processing frameworks such as Apache Spark (Databricks)</li><li>
Assist in processing and transforming structured and semi-structured data at scale</li></ul><p></p><p><b>
ETL/ELT Implementation</b></p><ul><li>
Assist in designing and implementing ETL/ELT processes for data integration and transformation.</li><li>
Contribute to the design and implementation of ETL/ELT workflows using Azure Data Factory, Databricks, or equivalent tools</li><li>
Support data ingestion from multiple sources (databases, APIs, files, cloud storage)</li></ul><p></p><p><b>
Cloud Integration &amp; Platform (Microsoft Azure)</b></p><ul><li>
Work with <b>Azure-native data services</b>, including:<ul><li>
Azure Data Factory</li><li>
Azure Synapse Analytics</li><li>
Azure Data Lake Storage (ADLS Gen2)</li><li>
Azure Databricks</li></ul></li><li>
Utilize cloud services such as Azure (Data Factory, Synapse, Data Lake), AWS (S3, Redshift, Glue), or Google Cloud Platform (BigQuery, Dataflow) for data storage and processing.</li><li>
Support secure configuration of cloud resources, access controls, and data storage</li></ul><p></p><p><b>
Database Management</b>:</p><ul><li>
Manage and query relational databases (e.g., PostgreSQL, MySQL, Oracle) and NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).</li><li>
Query and manage <b>relational databases</b> (Azure SQL, SQL Server, PostgreSQL, MySQL)</li><li>
Support analytics and reporting use cases using <b>modern data warehouse / lakehouse architectures</b></li></ul><p></p><p><b>
Data Warehousing</b>:</p><ul><li>
Support the development and optimization of modern data warehouse solutions like Databricks, Snowflake, Redshift, or BigQuery.</li></ul><p><b>
Pipeline Orchestration</b></p><ul><li>
Build and manage workflows using orchestration tools like Apache Airflow, Prefect, or Luigi.</li><li>
Assist with workflow orchestration using tools such as Azure Data Factory pipelines or Apache Airflow (where applicable)</li><li>
Support scheduling, monitoring, and failure handling of data pipelines</li></ul><p><b>
Big Data Tools</b></p><ul><li>
Work with distributed data systems and storage solutions like HDFS or cloud-native equivalents.</li></ul><p><b>
Version Control</b></p><ul><li>
Collaborate with the team using Git for code versioning and management.</li></ul><p><b>
Debugging and Optimization</b></p><ul><li>
Diagnose and resolve performance issues in data systems and optimize database queries.</li></ul><p><b>
DevOps, Quality &amp; Optimization</b></p><ul><li>
Collaborate using Git-based workflows (Azure DevOps Repos or GitHub)</li><li>
Support data quality checks, performance tuning, and query optimization</li><li>
Assist with documentation of data pipelines, schemas, and system design</li></ul><p></p><div><p>
Technical Requirements</p></div><p><b>
Skill Area</b></p><p><b>
Requirements</b></p><p><b>
Programming</b></p><ul><li>
Proficiency in Python- Experience with scripting languages for automation</li></ul><ul><li>
Solid understanding of <b>SQL</b> for data querying and transformation</li></ul><p><b>
Data Processing Frameworks</b></p><ul><li>
Hands-on experience with Apache Spark, Hadoop, or Apache Beam- Familiarity with ETL/ELT processes</li><li>
Understanding of ETL / ELT concepts and data pipeline design</li></ul><p><b>
Database and Querying</b></p><ul><li>
Strong understanding of SQL- Experience with relational databases (PostgreSQL, MySQL, Oracle)</li><li>
Experience with NoSQL databases (MongoDB, Cassandra, DynamoDB)</li></ul><p><b>
Cloud Platforms</b></p><ul><li>Familiarity with <b>Microsoft Azure data services</b></li></ul><ul><li>
Azure Data Factory</li><li>
Azure Synapse Analytics</li><li>
Azure Data Lake</li><li>
Azure Databricks</li></ul><p>
(Data Factory, Synapse, Data Lake)- AWS (S3, Redshift, Glue</p><ul><li>
Awareness of Azure security and identity concepts (RBAC, managed identities) is advantageous</li></ul><p><b>
Data Warehousing</b></p><ul><li>Experience with Databricks, Snowflake, Redshift, or BigQuery</li></ul><p><b>
Data Pipelines and Orchestration</b></p><ul><li>Knowledge of tools like Apache Airflow, Prefect, or Luigi</li></ul><p><b>
Big Data Tools</b></p><ul><li>Experience with distributed data systems and storage solutions like HDFS</li></ul><p><b>
Version Control</b></p><ul><li>Proficiency with Git for code versioning and collaboration</li></ul><p></p><p><b>
Preferred Qualifications</b></p><ul><li>
Exposure to <b>Azure DevOps</b> or <b>GitHub Actions</b></li><li>
Familiarity with Agile / Scrum delivery environments</li><li>
Interest in enterprise analytics, cloud platforms, and data governance</li><li>
Awareness of data privacy and governance principles (e.g., GDPR concepts)</li><li><b>
Note:</b> Multi-cloud exposure (AWS / GCP) is beneficial but <b>not required</b>. The primary environment is <b>Microsoft Azure</b>.</li><li><b>
Experience</b>: Practical exposure to building and optimizing scalable data pipelines, batch and real-time data processing.</li><li><b>
Debugging</b>: Familiarity with diagnosing and resolving performance issues in data systems.</li><li><b>
Data Governance</b>: Understanding of data privacy regulations (e.g., GDPR, CCPA) and experience implementing data quality checks and access controls.</li><li><b>
Certifications</b> (Optional but Valuable):<ul><li>
AWS Certified Data Analytics &ndash; Specialty</li><li>
Google Professional Data Engineer</li><li>
Microsoft Azure Data Engineer Associate</li><li>
Databricks Certified Data Engineer Associate</li></ul></li></ul><p></p><div><p>
Soft Skills</p></div><ul><li><b>
Problem-Solving</b>: Ability to troubleshoot complex data and system issues independently.</li><li><b>
Communication</b>: Collaborate with data analysts, scientists, and engineers to understand data needs and deliver solutions.</li><li><b>
Documentation</b>: Document data workflows, system designs, and troubleshooting procedures effectively.</li><li><b>
Team Collaboration</b>: Experience working in cross-functional teams using Agile or similar methodologies.</li></ul><p></p><div><p>
Education</p></div><ul><li>
Bachelor&rsquo;s degree (or final-year student) in <b>Computer Science, Data Engineering, Information Systems, Engineering, or a related field</b></li><li>
Relevant projects, internships, or practical experience may substitute for formal education</li></ul><p></p><div><p>
Learning Opportunities</p></div><ul><li>
Hands-on experience building data pipelines in a <b>Microsoft Azure enterprise environment</b></li><li>
Exposure to <b>lakehouse architectures, analytics platforms, and cloud security practices</b></li><li>
Practical experience with Databricks, Azure Data Factory, and Synapse</li><li>
Mentorship from senior data engineers and architects working on live programs</li><li>
Insight into how data engineering supports large-scale infrastructure, engineering, and program delivery</li></ul><p></p><p><b>
Duration</b></p><ul><li>
Internship duration: 3 to 6 months with possibility of extension.</li></ul><p></p>
Parsons equally employs representation at all job levels no matter the race, color, religion, sex (including pregnancy), national origin, age, disability or genetic information.<p></p><p>
We truly invest and care about our employee&rsquo;s wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest&mdash;APPLY TODAY!</p><p></p><div>
Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer to https://www.parsons.com/fraudulent-recruitment/.</div></div>
<br><div><div><div>COMPETITIVE BENEFIT OFFERINGS</div></div><div><div><div><br>
Financial Wellness</div><div><br>
We care about your financial wellbeing. Parsons offers competitive pay and retirement plans to help you build wealth for the future while giving you the flexibility to diversify your investments.</div></div><div><div>
Work Life Harmony</div><div><br>
Balance in life is important and time away from the office is imperative to allow you to refresh and focus your attention on the things that matter to you. Parsons supports your time away by providing paid time off and paid flexible holidays.</div></div><div><div>
Career Development</div><div><br>
We are committed to fostering the personal and professional growth of our employees. Develop and advance yourself though our comprehensive training, educational and mentorship programs.</div></div><div><div><br>
Veteran Support</div><div><br>
We provide Industry leading benefits to support veterans and active-duty members to provide security for you and your family by offering robust leave and benefits; including paid active-duty military leave and paid time off when transitioning back to civilian life.</div></div><div><div>
Mind &amp; Body</div><div><br>
At Parsons we inspire healthier habits, heathier minds, and a healthier you through our wellness program. Participate in our weekly Meditation Mondays and Wellness Wednesdays. Wellness, at Parsons, is more than just your annual checkup.</div></div><div><div>
Health</div><div><br>
Health is not a one size fits all. At Parsons, we offer a robust Employee Assistance Program as well as comprehensive medical, dental and vision plans through large, national carriers with the choice of regional PPO, HDHP, or HMO networks.</div></div></div></div><p></p>

Data Warehouse Engineer - Intern

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
As a Business Intelligence Engineer specializing in Cross-Border Business, you will drive data-led decision-making for Amazon&rsquo;s global expansion initiatives. You will partner with cross-functional teams to define key performance indicators (KPIs), build scalable data pipelines, and deliver actionable insights that optimize cross-border operations, pricing, logistics, and market entry strategies. This role requires deep technical expertise in data engineering, analytics, and visualization, coupled with a nuanced understanding of international market dynamics.<br>
<br>
Key Responsibilities<br>
<br>
Define and Track Cross-Border KPIs<br>
Collaborate with product, finance, and operations teams to identify and prioritize KPIs for cross-border business performance. Design dashboards and reports to monitor metrics such as sales growth, fulfillment efficiency, and regional profitability.<br>
<br>
Build Scalable Data Pipelines<br>
Develop and maintain ETL processes to ingest, transform, and analyze cross-border transactional data from diverse sources. Optimize data workflows for Amazon Redshift, Athena, or similar platforms to support real-time analytics.<br>
<br>
SQL and Advanced Analytics<br>
Write complex SQL queries to validate data integrity, automate reporting, and support tests for cross-border initiatives. Apply statistical methods to analyze regional market trends and customer behavior.<br>
<br>
Cross-Functional Partnership<br>
Translate ambiguous business questions from global stakeholders into measurable data solutions. Lead investigations into operational anomalies and recommend process improvements.<br>
<br>
Data Visualization and Storytelling<br>
Create interactive dashboards to communicate insights to non-technical audiences. Highlight conversion funnel drop-off points and propose data-driven strategies for improvement.</p><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience</li><li>Experience with data visualization using Tableau, Quicksight, or similar tools</li><li>Experience with data modeling, warehousing and building ETL pipelines</li><li>Experience in Statistical Analysis packages such as R, SAS and Matlab</li><li>Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift</li><li>Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets</li></ul><br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Business Intelligence Engineer (BIE II), AMET Crossborder Business

Naffco

<div><h4 class="jobSectionHeader"><b>Job Summary</b></h4><p>
We are seeking an experienced <b>Data Scientist</b> with strong capabilities in data analytics, statistical modeling, and data visualization to support enterprise reporting and strategic decision-making. The role involves working with large, structured datasets, developing advanced analytical models, and creating intuitive dashboards to translate data into actionable business insights. The ideal candidate will have hands-on experience with <b>Qlik Sense</b> for reporting and dashboard development, along with strong SQL skills for data extraction and transformation. Experience with <b>Oracle EBS</b> data is highly desirable. The role requires collaboration with business stakeholders, IT teams, and management to ensure accurate, timely, and meaningful data-driven insights.</p><h4 class="jobSectionHeader"><b>
Key Responsibilities:</b></h4><ul><li><p>
Design, develop, and maintain interactive dashboards and reports using Qlik Sense to enable data-driven decision-making.</p></li><li><p>
Build predictive, statistical, and analytical models to support operational, tactical, and strategic business decisions.</p></li><li><p>
Write and optimize SQL queries to extract, transform, and analyze large datasets efficiently.</p></li><li><p>
Ensure data integrity, consistency, and high performance across analytics solutions.</p></li><li><p>
Collaborate with business units to understand reporting needs and translate them into technical solutions.</p></li><li><p>
Support ongoing enhancements, troubleshooting, and optimization of data models, dashboards, and reports.</p></li><li><p>
Stay updated with emerging tools, techniques, and best practices in data analytics and business intelligence.</p></li></ul><h4 class="jobSectionHeader"><b>
Qualifications &amp; Experience:</b></h4><ul><li><p>
BTech / BSc in Computer Science, MCA, or equivalent technical qualification.</p></li><li><p>
2&ndash;5 years of proven experience in data analytics, modeling, and dashboard development.</p></li><li><p>
Strong expertise in <b>Qlik Sense</b> and <b>SQL</b>; experience with <b>Oracle EBS</b> is a plus.</p></li><li><p>
Excellent analytical, problem-solving, and communication skills, with the ability to present complex data clearly to stakeholders.</p></li><li><p>
Ability to work independently as well as collaboratively in a dynamic, fast-paced environment.</p></li></ul></div><p></p>

Data Scientist

Delivery Hero

<div><b>Company Description</b><p><br>
Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat&rsquo;s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.<br>
</p><p>We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.<br>
</p><p>Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.</p><b><br>
Job Description</b><p><br>
As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.</p><p>
As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data through building machine learning models at scale. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.</p><p><b>
Responsibilities</b></p><ul><li><p>
Leveraging ambiguous business problems as opportunities to drive objective criteria using data.</p></li><li><p>
Solving complex business problems using the simplest most appropriate Algorithms to deliver business value.</p></li><li><p>
Designing and implementing effective and impactful machine learning systems in production.</p></li><li><p>
Developing a deep understanding of the product experiences and business processes that make up your area of focus.</p></li><li><p>
Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.</p></li><li><p>
Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.</p></li><li><p>
Working closely with product and business teams to identify important questions that can be answered effectively with data.</p></li><li><p>
Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.</p></li><li><p>
Designing, planning, and analyzing experiments (A/B and multivariate tests).</p></li><li><p>
Supporting product and business managers with KPI design and goal setting.</p></li><li><p>
Mentoring other data scientists in their growth journeys.</p></li><li><p>
Contributing to improving our ways of work, our tooling, and our internal training programs.</p></li></ul><b><br>
Qualifications</b><p><b><br>
Technical Experience</b></p><ul><li><p>
Experience in machine learning, deep learning, recommendation/personalization systems, pattern recognition, data mining and artificial intelligence.</p></li><li><p>
Deep knowledge and experience in ML algorithms and frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch ...).</p></li><li><p>
Excellent SQL.</p></li><li><p>
Competence with reproducible data analysis using Python or R.</p></li><li><p>
Familiarity with data modeling and dimensional design.</p></li><li><p>
Strong command over the entire data lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.</p></li><li><p>
Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.</p></li><li><p>
Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.</p></li><li><p>
Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).</p></li><li><p>
Familiarity with BigQuery and the Google Cloud Platform is a plus.</p></li><li><p>
Data engineering and data pipeline development experience (e.g. via Airflow)</p></li></ul><p><b>
Qualifications</b></p><ul><li><p>
Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.</p></li><li><p>
6+ years of experience working in data science, machine learning, and Gen AI.</p></li><li><p>
Experience doing data science in an online consumer product setting is a plus.</p></li><li><p>
A good problem solver with a &lsquo;figure it out&rsquo; growth mindset.</p></li><li><p>
An excellent collaborator.</p></li><li><p>
An excellent communicator.</p></li><li><p>
A strong sense of ownership and accountability.</p></li><li><p>
A &lsquo;keep it simple&rsquo; approach to #makeithappen.</p></li></ul></div>

Staff Data Scientist, Algorithms, ML

SilentEight

<div><p>At Silent Eight, we develop our own AI-based products to combat financial crimes that enable things like money laundering, the financing of terrorism, and systemic corruption. We&rsquo;re a leading RegTech firm working with large international financial institutions such as Standard Chartered Bank and HSBC. Join us and help make the world a safer place!<br>
<br>
<br>
</p><p>As a <b>Data Scientist</b>, you will own the end-to-end development of data solutions &mdash; from understanding business problems to deploying and maintaining models in production. You&rsquo;ll work closely with customers and internal teams to build impactful, scalable solutions using machine learning, NLP, and other advanced techniques.</p><h4 class="jobSectionHeader"><b>
Responsibilities</b></h4><ul><li><p>
Lead the data science lifecycle, from discovery and exploration to delivery and customer hand-off.</p></li><li><p>
Translate ambiguous business problems into clear problem statements and deliver working, production-ready solutions.</p></li><li><p>
Partner with customers and internal stakeholders to co-design use cases, define success criteria, and ensure models are adopted and successful in production.</p></li><li><p>
Build quick, iterative prototypes to test ideas, and work cross-functionally to deploy validated solutions into production environments.</p></li><li><p>
Own and improve pipelines for data integration, validation, and monitoring, ensuring long-term stability and performance.</p></li><li><p>
Analyze large-scale structured and unstructured datasets to extract insights and power model development.</p></li><li><p>
Apply machine learning, NLP, graph analytics, and other advanced techniques to solve challenging problems such as semantic search, or anomaly detection.</p></li><li><p>
Create and maintain internal data science tooling to streamline experimentation, testing, and delivery.</p></li><li><p>
Support internal teams and customers with issue resolution, ensuring data science solutions continue to deliver value post-deployment.</p></li><li><p>
Follow and advocate for best practices in MLOps, DataOps, and clean code to ensure reproducibility, maintainability, and scalability.</p></li></ul><h4 class="jobSectionHeader"><b>
Requirements</b></h4><ul><li><p><br>
Based in the United Arab Emirates (remote-first team; flexible working environment).</p></li><li><p>
Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, or a related field.</p></li><li><p>
3-5 years of demonstrated experience with LLM technologies (LangChain, LlamaIndex, OpenAI APIs, etc.) and building NLP applications.</p></li><li><p>
Deep proficiency in Python: you write clean, modular, maintainable, and testable code suitable for real-world deployments.</p></li><li><p>
Solid SQL skills and hands-on experience with large-scale data (e.g., PySpark, BigQuery).</p></li><li><p>
Skilled in graph analysis, machine learning, and unstructured data workflows.</p></li><li><p>
Demonstrated ability to apply software engineering best practices (e.g., modular design, clean code, unit testing, CI/CD) in data science and machine learning projects, ensuring production-readiness and maintainability.</p></li><li><p>
Ability to drive end-to-end initiatives, from exploration to delivery, where solutions must be state-of-the-art, business-aligned, and regulatory-compliant.</p></li><li><p>
Comfortable working in Linux environments and using collaborative tools (e.g., Git, Docker).</p></li><li><p>
Strong communication skills&mdash;translate technical complexity into actionable business narratives, driving clarity, alignment, and decision-making across all levels of the organization.</p></li><li><p>
Mindset of ownership: you&rsquo;re excited to see projects through, from first prototype to deployed, customer-facing solution.</p></li></ul><h4 class="jobSectionHeader"><b>
We offer:</b></h4><ul><li><p>
Full time employment</p></li><li><p>
Employee benefits</p></li><li><p>
Work-life balance: flexible working hours, remote work forever</p></li><li><p>
Career growth: Promotion and great development opportunities within the organization</p></li></ul></div><p></p>

Explore 518+ Data engineer in Dubai this February. Find roles across top companies and apply now to boost your career.

518 data engineer jobs In Dubai

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