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Course: Effective Business Decisions Using Data Analysis

Dubai, Dubai Europeanqualitytc

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Effective Business Decisions Using Data Analysis

ID 257

Course: Effective Business Decisions Using Data Analysis

This interactive, applications-driven 5-day course will highlight the added value that data analytics can offer a professional as a decision support tool in management decision making. It will show the use of data analytics to support strategic initiatives; to inform on policy information; and to direct operational decision making. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management decision making. Exposure to the discipline of data analytics will ultimately promote greater confidence in the use of evidence-based information to support management decision making.

This course will feature:
  • Discussions on applications of data analytics in management
  • The importance of data in data analytics
  • Applying data analytical methods through worked examples
  • Focusing on management interpretation of statistical evidence
  • How to integrate statistical thinking into the work domain
What are the Goals? By the end of this course, participants will be able to:
  • Explain the scope and structure of data analytics.
  • Apply a cross-section of useful data analytics.
  • Interpret meaningfully and critically assess statistical evidence.
  • Identify relevant applications of data analytics in practice.
Who is this Course for? This course is suitable to a wide range of professionals but will greatly benefit:
  • Professionals in management support roles
  • Analysts who typically encounter data/analytical information regularly in their work environment
  • Those who seek to derive greater decision-making value from data analytics
How will this be Presented?

This course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension, and retention of the information presented. The daily workshops will be highly interactive and participative. This involves regular discussion of applications as well as hands-on exposure to data analytics techniques using Microsoft Excel. Delegates are strongly encouraged to bring and analyse data from their own work domain. This adds greater relevancy to the content. Emphasis is also placed on the valid interpretation of statistical evidence in a management context.

The Course Content
  • Day One: Setting the Statistical Scene in Management
    • Introduction; The quantitative landscape in management
    • Thinking statistically about applications in management (identifying KPIs)
    • The integrative elements of data analytics
    • Data: The raw material of data analytics (types, quality, and data preparation)
    • Exploratory data analysis using Excel (pivot tables)
    • Using summary tables and visual displays to profile sample data
  • Day Two: Evidence-based Observational Decision Making
    • Numeric descriptors to profile numeric sample data
    • Central and non-central location measures
    • Quantifying dispersion in sample data
    • Examine the distribution of numeric measures (skewness and bimodal)
    • Exploring relationships between numeric descriptors
    • Breakdown analysis of numeric measures
  • Day Three: Statistical Decision Making – Drawing Inferences from Sample Data
    • The foundations of statistical inference
    • Quantifying uncertainty in data – the normal probability distribution
    • The importance of sampling in inferential analysis
    • Sampling methods (random-based sampling techniques)
    • Understanding the sampling distribution concept
    • Confidence interval estimation
  • Day Four: Statistical Decision Making – Drawing Inferences from Hypotheses Testing
    • The rationale of hypotheses testing
    • The hypothesis testing process and types of errors
    • Single population tests (tests for a single mean)
    • Two independent population tests of means
    • Matched pairs test scenarios
    • Comparing means across multiple populations
  • Day Five: Predictive Decision Making - Statistical Modeling and Data Mining
    • Exploiting statistical relationships to build prediction-based models
    • Model building using regression analysis
    • Model building process – the rationale and evaluation of regression models
    • Data mining overview – its evolution
    • Descriptive data mining – applications in management
    • Predictive (goal-directed) data mining – management applications
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Senior AI Engineer - Data & Infrastructure for Multimodal Models (100% Remote)

Dubai, Dubai Tether Operations Limited

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Join Tether and Shape the Future of Digital Finance

At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.

Innovate with Tether

Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.

But that’s just the beginning:

Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.

Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing.

Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.

Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.

Why Join Us?

Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.

If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.

Are you ready to be part of the future?

About the job

We're seeking experienced AI infrastructure Engineers to design and implement robust, scalable pipelines for massive data workloads. Join Tether’s applied research team, where you’ll contribute to high-impact projects that run across thousands of GPUs and drive cutting-edge video generation foundation development.

Responsibilities

  • Build and scale high-throughput data infrastructure optimized for video and multimodal content processing across large GPU clusters (e.g., H100/H200).

  • Design core preprocessing algorithms for video, audio, text, and image modalities, enabling efficient extraction, synchronization, and normalization of temporal data.

  • Build automated acquisition pipelines for sourcing large-scale video datasets, handling diverse formats, frame rates, annotations, and embedded audio.

  • Architect robust systems for scalable evaluation and annotation, including prompt-based scoring, perceptual metrics, caption generation, and retrieval-based diagnostics.

  • Collaborate with model researchers to co-design video model architectures (e.g. DiTs, VAEs, spatio-temporal transformers) and training schedules across pretraining and fine-tuning stages.

  • Optimize distributed data loading and pipeline throughput for training at scale, ensuring robustness across model variants and modality combinations.

  • Manage infrastructure to support experiment tracking, model versioning, and cross-team deployment workflows, integrating with production and research platforms.

  • Support backend engineering across research, product, and creative teams to ensure seamless integration of data and model workflows from prototyping to inference.

  • Proficient in Python with strong programming skills across backend, infrastructure, and data tooling domains.

  • Strong software engineering experience, including 2+ years working with petabyte-scale data pipelines and systems across thousands of GPUs.

  • Proven ability to architect and maintain large-scale distributed systems for data processing and delivery.

  • Deep expertise in orchestration frameworks such as Kubernetes and SLURM with hands-on experience deploying and managing high-throughput workloads.

Preferred Qualifications

  • Practical experience on building pipelines and infrastructure with visual and multimodal datasets, including image/video pipelines.

  • Experience in building video foundation infrastructure pipelines and workflows with collaboration of LLM and/or video foundation research and engineering teams is a strong advantage.

Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:

  • Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page:

  • Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.

  • Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.

  • Double-check email addresses. All communication from us will come from emails ending in @ tether.to or@ tether.io

  • We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.

When in doubt, feel free to reach out through our official website.

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Business Analysis and Data Analyst

Dubai, Dubai micro1

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Overview

Job Title: Business Data Analyst (Banking) - Digital Transformation

Job Type: Full-Time Contract (1 year, renewable)

Location: On-site, Dubai, Dubai, United Arab Emirates

Job Summary:

Join our team as a Business Data Analyst at the forefront of digital transformation within a leading UAE bank. In this pivotal role, you will bridge business stakeholders and technology teams, applying deep analytical expertise to drive insights, optimize processes, and elevate customer journeys across key digital banking initiatives. Embrace an asynchronous work culture that values exceptional written communication and proactive problem-solving.

Key Responsibilities
  • Elicit, analyze, and document business requirements, user stories, and process flows for digital projects.
  • Act as a key liaison between business units and technical teams to ensure clear understanding of project objectives.
  • Conduct gap analysis and impact assessments for new features and system changes within core banking functions.
  • Participate in Agile/Scrum ceremonies, including sprint planning, backlog grooming, and daily stand-ups.
  • Design and execute test scenarios, supporting user acceptance testing (UAT) and solution validation.
  • Write complex SQL queries to extract and analyze large datasets, generating actionable insights and KPI reports with Power BI.
  • Translate analytical findings into clear, data-driven recommendations and presentations for diverse stakeholders.
Required Skills and Qualifications
  • Bachelor’s degree in Computer Science, Engineering, Finance, Business, or a quantitative discipline.
  • 5-9 years’ experience as a Business Analyst, with a strong background in Banking, Financial Services, or FinTech.
  • High proficiency in SQL and PL/SQL, with hands-on experience in Power BI for data visualization.
  • Proven experience working with core-banking systems and exposure to digital transformation projects.
  • Solid understanding of Agile methodologies (Scrum, Kanban) and expertise with JIRA.
  • Exceptional written communication skills, adept at working in asynchronous, collaborative environments.
  • Strong analytical and critical thinking abilities with excellent stakeholder management.
Preferred Qualifications
  • Relevant professional certifications (CBAP, PMI-PBA, Agile Scrum, Data Analytics).
  • Experience with data modeling, Python or R for advanced analytics, and systems like Flexcube or OFSAA.
  • Expertise in digital banking products, customer journey mapping, and process optimization.

Become part of our team and contribute to high-impact initiatives, working on projects that set industry standards and drive meaningful change. We foster an inclusive, high-performing culture offering career development opportunities, comprehensive benefits, and a collaborative environment to help you thrive.

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