What Jobs are available for Data Science Positions in Dubai?

We are seeking a Senior Data Science Engineer with expertise in building and operationalizing production-grade machine learning pipelines . The ideal candidate will have hands-on experience with MLFlow, Databricks, and Azure ML , and a strong background in developing ML solutions for healthcare predictive use cases . This role will be central to embedding ML models into enterprise data workflows and ensuring their ongoing performance.

• ML Pipeline Engineering : Design, build, and maintain scalable ML pipelines leveraging MLFlow, Databricks, and Azure ML.

• Model Development : Develop and optimize ML models, particularly for healthcare predictive analytics .

• Integration : Embed ML models into KPI-driven data processing and analytics workflows .

• Model Lifecycle Management : Implement model monitoring, drift detection, retraining, and continuous improvement strategies.

• Collaboration : Work closely with data engineers, data scientists, and business stakeholders to deploy solutions that deliver measurable impact.

• 6+ years of experience in machine learning engineering or applied data science .

• Hands-on expertise with MLFlow, Databricks, and Azure ML .

• Strong experience in developing and deploying predictive ML models , ideally within healthcare.

• Proficiency in Python, SQL, PySpark , and modern ML frameworks (TensorFlow, PyTorch, or Scikit-learn).

• Knowledge of model monitoring, drift detection, and automated retraining strategies .

• Familiarity with cloud-native ML architectures and CI/CD for ML (MLOps).

• Strong problem-solving and collaboration skills with a focus on production-grade delivery.

• Work on cutting-edge healthcare predictive analytics solutions .

• Gain exposure to enterprise-scale ML pipelines on modern platforms.

• Opportunity to drive end-to-end ML lifecycle ownership .

• Competitive compensation and career growth in a fast-growing data-driven organization.

Overview

MAIN OBJECTIVE OF ROLE To define and drive the enterprise strategy for extracting business value from data by leveraging advanced analytics, machine learning, and artificial intelligence to generate insights, develop predictive models, foster AI innovation, and integrate ethical and scalable AI into products, services, and decision-making processes that deliver competitive advantage.

• Leads the development and implementation of machine learning models, algorithms, and AI systems and explores innovative approaches to solving business problems using AI technologies.
• Drives continuous process improvement and optimization by staying informed about advancements in data engineering and AI, recommending new tools and technologies.
• Builds, mentors, and leads a team of data and machine learning engineers, and AI specialists by providing guidance, support, and professional development opportunities to team members.
• Develops and executes the organization’s data science and AI vision, ensuring alignment with business objectives and measurable outcomes.
• Identifies, designs, and implements AI and machine learning solutions that enhance products, services, and operational efficiency.
• Establishes frameworks for responsible, explainable, and bias-free AI use in compliance with regulations and ethical standards.
• Partners with product owners, business leaders, and data engineering teams to ensure AI initiatives are integrated, scalable, and business-driven.
• Monitors advances in AI research, tools, and technologies, proactively applying them to maintain competitive advantage.
• Defines KPIs and tracks ROI for AI initiatives to ensure value delivery and continuous improvement.
• Acts as a “data translator,” bridging technical and business domains to convert complex challenges into actionable AI-driven outcomes.

• Bachelor's Degree (3+ years)
• Degree in Information Technology, Computer Science, Data Science, or related field
• Fluent in English
• Deep understanding of data governance, compliance, and security best practices. Excellent understanding of machine learning concepts and algorithms. Proven track record of delivering AI solutions from concept to production at enterprise scale. Strong background in statistical modeling, machine learning, deep learning, and AI productization. Demonstrated success in translating business strategy into AI-driven initiatives with measurable ROI. Experience in regulated industries (e.g., Airline) preferred, with a strong understanding of ethical and compliant AI practices.
• Years with qualifications: 10 - 12 years
• Google Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate are an advantage

• Customer Focus
• Teamwork
• Effective Communication
• Personal Accountability & Commitment to achieve
• Resilience & Flexibility (Can do attitude)
• Decision Making
• Inspiring & Developing Others
• Strategic Thinking
• Business Acumen

Reads and complies with the ISR policies of the Company and diligently reports any weakness or incidents to the respective Line Manager or the Information Security team. Completes all required ISR awareness sessions and follows associated guidelines in the day-to-day business operations.

Data Science Manager - Customer | Al-Futtaim Automotive

Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United Arab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organization to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.

By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day

Overview of the role
As a Data Science Manager (Customer) at Al-Futtaim Automotive, you will lead customer-centric AI and advanced analytics initiatives that drive marketing performance and enhance the customer experience. This role focuses on building predictive models, customer insights, and hyper-personalization solutions that create measurable business impact.

What you will do

• Build and deploy predictive models such as lead scoring, precision marketing, marketing attribution, customer segmentation, and hyper-personalization.
• Standardize and optimize marketing performance KPIs across brands using advanced statistical methods and data visualization.
• Deliver actionable customer insights through cohort analysis, customer lifetime value modelling, churn prediction, and campaign performance analysis.
• Collaborate with stakeholders to identify, define, and prioritize high-impact use cases supported by data-driven business cases.
• Lead and mentor a team of data scientists to deliver scalable AI/ML solutions that directly improve marketing ROI and customer experience.

Required skills to be successful

• Advanced knowledge of ensemble methods, gradient boosting, uplift modelling, and multi-arm bandits for marketing optimization.
• Expertise in attribution models (Markov chains, Shapley values), clustering techniques, recommender systems, and hyper-personalization.
• Proficiency in NLP, reinforcement learning, cohort analysis, lifetime value modelling, and churn prediction.
• Strong problem-solving skills and the ability to translate complex data science solutions into business value.
• Excellent stakeholder management, communication, and project management capabilities.

About the team
You will report to the Head of Customer Data Science and lead a small team comprising a Data Science Manager and Data Scientists. The team plays a pivotal role within the Finance Department at Al-Futtaim Automotive, driving innovation in customer analytics and marketing science.

What equips you for the role

• Bachelor’s, Master’s, or PhD in Marketing Analytics, Computer Science, or a related field.
• 7+ years of experience in customer analytics, data science, and AI/ML solutions.
• Hands-on expertise with machine learning techniques including CNNs, RNNs, LSTMs, time series forecasting, survival analysis, graph neural networks, Bayesian and causal modelling.
• Skilled in Python, SQL, Databricks, and modern ML libraries (scikit-learn, TensorFlow, PyTorch, Prophet, ARIMA/SARIMA).
• Proficient in CRM systems, marketing analytics platforms, and MLOps practices.
• Experience with LLMs, RAGs, and modern AI-based recommendation systems.
• Strong leadership skills to manage and mentor a data science team.

About Al-Futtaim Automotive
A major division of the UAE-based Al-Futtaim Group of companies, Al-Futtaim Automotive is an industry leader with presence in 10 countries across the Middle East, Asia and Africa. Our core business activities at Al-Futtaim Automotive include distribution, manufacturing, leasing and aftersales, and we are firmly established as the regional representative of some of the world’s most iconic automotive brands: Toyota, Lexus, Honda, Jeep, Chrysler, Dodge, Volvo and RAM. We are driven by a customer-centric approach, constantly pushing the boundaries on innovation, quality standards, and value-added service across our vast universe of customers - right from motoring enthusiasts to fleet operators to contractors. Our mission is to become the leader in custom-made mobility solutions by delivering nothing less than world-class omni-channel experiences. We channel our local expertise and global trust to deliver one of the most comprehensive portfolios of mobility products and solutions, from passenger cars to SUVs, electric vehicles to high-performance motorbikes, commercial vehicles to industrial & construction equipment. What keeps the company moving forward is a 9000-member strong team, with inspiring possibilities for growth, throughout the career path. This is Al-Futtaim Automotive and we empower talent to move forward.

Data Science Manager - Finance | Al-Futtaim Automotive

Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United Arab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organization to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.

By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day

As a Data Science Manager(Finance) at Al-Futtaim Automotive, you will lead AI and data science initiatives that optimize financial performance, strengthen risk management, and improve business decision-making. This role focuses on advanced predictive modelling, financial forecasting, and portfolio optimization to create measurable impact across the organization

• Build and deploy predictive models for residual value optimization, credit risk scoring, probability of default, and F&I leasing pricing optimization.
• Standardize financial KPIs and risk dashboards using statistical process control and advanced visualization tools.
• Generate financial insights through time series analysis, portfolio optimization, survival analysis, and risk modelling.
• Collaborate with finance and risk teams to identify and prioritize high-potential data-driven use cases.
• Lead and mentor a team of data scientists, ensuring the delivery of scalable machine learning and AI models

• Advanced expertise in time series forecasting, regression, logistic regression, and random forests.
• Strong skills in survival analysis, neural networks, reinforcement learning, and genetic algorithms.
• Deep knowledge of portfolio optimization, risk modelling, and causal inference techniques.
• Proficiency in deep learning (CNNs, RNNs, LSTMs, Transformers) and advanced pattern recognition.
• Strong understanding of financial regulations and their impact on AI/ML model development.
• Excellent stakeholder management and ability to translate complex financial models into actionable insights

You will report to the Head of Financial Data Science and lead a team of Data Scientists and a Data Science Manager. The team operates within the Finance Department, playing a critical role in enhancing financial planning, risk management, and profitability through advanced analytics

• Bachelor’s, Master’s, or PhD in Financial Analytics, Computer Science, or related field.
• 7+ years of experience in financial analytics, data science, and machine learning.
• Hands-on expertise in advanced statistics, optimization, causal and Bayesian modelling, time series forecasting, Monte Carlo simulations, graph neural networks, and recommender systems.
• Proficient in Python, SQL, Databricks, and ML libraries (TensorFlow, PyTorch, Scikit-learn, ARIMA/SARIMA, Prophet).
• Knowledge of NLP, autoencoders, transformers, NER, computer vision (OpenCV, YOLO), and model explainability (SHAP, LIME).
• Experience with MLOps, Git, and visualization tools (Matplotlib, Seaborn, Plotly).
• Strong leadership, problem-solving, and communication skills to manage teams and deliver business impact.

About Al-Futtaim Automotive : A major division of the UAE-based Al-Futtaim Group of companies, Al-Futtaim Automotive is an industry leader with presence in 10 countries across the Middle East, Asia and Africa. Our core business activities at Al-Futtaim Automotive include distribution, manufacturing, leasing and aftersales, and we are firmly established as the regional representative of some of the world’s most iconic automotive brands: Toyota, Lexus, Honda, Jeep, Chrysler, Dodge, Volvo and RAM. We are driven by a customer-centric approach, constantly pushing the boundaries on innovation, quality standards, and value-added service across our vast universe of customers - right from motoring enthusiasts to fleet operators to contractors. Our mission is to become the leader in custom-made mobility solutions by delivering nothing less than world-class omni-channel experiences. We channel our local expertise and global trust to deliver one of the most comprehensive portfolios of mobility products and solutions, from passenger cars to SUVs, electric vehicles to high-performance motorbikes, commercial vehicles to industrial & construction equipment. What keeps the company moving forward is a 9000-member strong team, with inspiring possibilities for growth, throughout the career path. This is Al-Futtaim Automotive and we empower talent to move forward.

Overview

Data Science Manager (Operations) at Al-Futtaim Automotive leads AI and advanced analytics initiatives that transform operational performance across the business. This role focuses on predictive modelling, anomaly detection, and process optimization to drive efficiency, reduce costs, and enhance customer satisfaction.

• Build and deploy predictive models for price elasticity, predictive maintenance, churn prediction, and anomaly detection in parts utilization.
• Standardize operational KPIs and real-time reporting systems across brands using statistical process control and advanced visualization techniques.
• Deliver actionable insights on sales and operational performance using causal inference, A/B testing, and counterfactual models.
• Collaborate with cross-functional stakeholders to identify new use cases, define business cases, and prioritize high-impact initiatives.
• Lead and mentor a team of data scientists, ensuring robust MLOps practices and scalable model deployment.

• Expertise in time series analysis, regression, and survival analysis for price elasticity and churn prediction.
• Proficiency in IoT data analysis, predictive maintenance algorithms, and unsupervised learning techniques for anomaly detection.
• Strong knowledge of causal inference, A/B testing, counterfactual modelling, and optimization algorithms.
• Familiarity with deep learning frameworks and pattern recognition for complex operational data.
• Strong stakeholder engagement and the ability to turn complex data insights into operational improvements.

You will report to the Head of AI and Data Science for Operational Excellence and lead a team of Data Scientists and a Data Science Manager. The team works within the Finance Department, playing a key role in improving efficiency, reducing risk, and unlocking value across all operational functions.

• Bachelor’s, Master’s, or PhD in Computer Science, Statistics, or a related field.
• 7+ years of experience in data science, operations analytics, or AI-driven business transformation.
• Hands-on expertise with advanced statistics, optimization, survival analysis, causal and Bayesian modelling, time series forecasting, graph neural networks, and recommender systems.
• Proficient in Python, SQL, Databricks, and ML libraries (TensorFlow, PyTorch, Scikit-learn, ARIMA/SARIMA, Prophet).
• Knowledge of NLP, transformers, autoencoders, NER, computer vision (OpenCV, YOLO), and model explainability (SHAP, LIME).
• Experience with MLOps, Git, and visualization tools (Matplotlib, Seaborn, Plotly).
• Strong leadership, communication, and project management skills.

A major division of the UAE-based Al-Futtaim Group of companies, Al-Futtaim Automotive is an industry leader with presence in 10 countries across the Middle East, Asia and Africa. Our core business activities include distribution, manufacturing, leasing and aftersales, and we are the regional representative of brands such as Toyota, Lexus, Honda, Jeep, Chrysler, Dodge, Volvo and RAM. We are driven by a customer-centric approach, pushing innovation, quality standards, and value-added service across our customer base. Our mission is to become the leader in mobility solutions by delivering world-class omni-channel experiences. We employ a 9,000-member team with growth opportunities across the career path. This is Al-Futtaim Automotive and we empower talent to move forward.

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.

• 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

• 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.

• 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

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.

• 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

В формирующееся направления Data Science ищем опытного Data Scientist , который сможет эффективно взаимодействовать с другими командами, генерировать и проверять гипотезы, а успешные решения внедрять в продукт.

По мере роста команды и появления интересов в конкретных направлениях, будет возможность стать тимлидом.

У компании разные бизнес-направления (склады с логистикой, маркетплейсы), поэтому могут быть разнообразные задачи : от оптимизации процессов на складах до рекомендаций при поиске товаров и разработки чат-ботов.

EMEX — международный холдинг, который включает торговый, информационный, и фулфилмент бизнесы: EMEX.DWC в ОАЭ, фулфилмент оператор HWC и EMEX.ru.

EMEX — стабильный бизнес: на протяжении 20+ лет мы прибыльны каждый квартал . Сейчас у бизнеса есть задача — быть эффективным , а для этого нужно достичь промежуточных целей по измеримости и управляемости. Для этого мы перепроектируем структуру всех компаний и значительно усиливаем все наши направления.

• Разработка новых решений (ML-модели, оптимизационные модели и т.д.)
• Взаимодействие с другими командами (презентация результатов, выявление потребностей, валидация гипотез).

• У тебя большой опыт работы в Data Science и ты знаком со всем основным теоретическим (мат.статистика, методологии тестирования, ml-модели, теория оптимизации) и технологическим стеком (Python: pandas, scikit-learn, sciPy, etc.). Ты работаешь в сфере DS более 3 лет и у тебя техническое образование;
• Ты готов работать руками и не боишься сырых данных. Отлично знаешь SQL, возможно даже имеешь опыт работы в BI-системах;
• Ты проактивен и не боишься экспериментировать. Для тебя естественны желания протестировать новый алгоритм на основе прочитанной статьи, найти неэффективность в процессе и смоделировать альтернативный процесс, покопаться в данных и затем сформулировать новые гипотезы;
• Ты ориентирован на бизнес-результат и не стремишься все решать только с помощью ml-модели. У тебя прокачено критическое мышление и problem solving, ты можешь оценить свое решение с точки зрения бизнеса;
• Ты четко доносишь свои мысли и можешь доступно презентовать результаты. Для тебя не проблема объяснить смысл ROC-AUC коллеге, визуализировать результат с помощью понятного графика или презентовать новую статью.

• Ты работал в фулфилменте (хранение, сортировка, логистика) или в маркетплейсах и классифайдах;
• Ты занимался задачами комбинаторной оптимизации или задачами рекомендаций и поиска;
• У тебя за спиной несколько ML-проектов полного цикла.

Удаленный формат работы из любой страны мира. С нами можно работать по ТК РФ (оплата в рублях) или через контракт через Дубай (оплата в USD);

Возможность быстро расти . Сейчас есть много вакуума ответственности, который можно занимать;

Международный продукт , улучшающий потребительский опыт предпринимателей в разных странах, с большими амбициями и ресурсами для дальнейшего глобального развития;

Работу с высоким уровнем свободы , возможность принимать решения и выбирать пути решения задач самостоятельно;

Отсутствие бюрократии.

COMPANY DESCRIPTION

We are the world’s largest performance marketing network, with over 3,000 experts in 68 offices in 48 markets. We offer a complete suite of crafts designed to deliver customer-centric performance marketing solutions. Armed with intelligent insights and an audience first approach our team of expert consultants deliver integrated media, data and technology solutions that help brands better connect with consumers at every stage of their digital marketing transformation.

In MENA, Kinesso are the Digital Marketing Transformation experts and provide services focused on delivering marketing efficiencies and return of investment for brands across the MENA region.

ROLE OVERVIEW

At Kinesso, we rely on powerfully insightful data to help brands better connect with their consumers at every stage of their marketing transformation.

Our data science team has mathematical and statistical expertise, natural curiosity, and a creative mind that’s not so easy to find. As a data scientist you mine, interpret, and clean data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. And will “slice and dice” data using your own methods, creating new visions for the future.

OBJECTIVES

• Collaborate with advertiser’s brand team and media agencies to develop an understanding of needs.
• Research and devise innovative statistical models for data analysis.
• Communicate findings and insights effectively to both technical and non-technical stakeholders through reports, presentations, and visualizations.
• Enable smarter business processes—and implement analytics for meaningful insights.
• Become a thought leader on the value of data by finding new features or products by unlocking the value of data.
• Develop and implement machine learning models and algorithms to solve complex business problems.
• Stay up-to-date with the latest advancements in data science, machine learning, and AI technologies .
• Work with product and engineering teams to integrate data science solutions into production systems
• Collaborate with data engineers to design and optimize data pipelines and architectures.

• Keep current with technology and industry developments.

RESPONSIBILITIES

• Analyse data for trends and patterns using machine learning algorithms and Interpret data with a clear objective in mind.
• Identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the team to strategize and execute the development of data products.
• Conduct exploratory data analysis to identify trends, patterns, and opportunities for improvement.
• Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
• Working on the Media Mix Models , Full Funnel Model, Multitouch Attribution etc. to optimize the media
• Devise and utilize algorithms and models to mine data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
• Conduct causality experiments by applying A/B experiments to identify the root issues of an observed result.
• Communicate analytic al solutions to stakeholders and implement improvements as needed.

SKILLS & QUALIFICATIONS

• Bachelor’s degree in statistics, applied mathematics, or related discipline.
• Minimum of 4-6 years in a similar role.
• Proficiency with data mining, mathematics, and statistical analysis
• Advanced pattern recognition and predictive modelling experience
• E xperience of Media Mix Models, Multitouch Attribution on the working knowledge
• Media understanding is preferrable
• Additional skills of Gen AI, NLP, NLU are optional/ added advantage
• Experience with Excel, Tableau /Looker Studio , SQL, and languages: Python, R
• Storytelling and Data Visualization
• Media understanding is preferrable
• Additional skills of Gen AI, NLP, NLU are optional/ added advantage
• Working knowledge of supervised and unsupervised machine learning techniques such as regression, clustering, classification, decision tree learning, and artificial neural networks
• Comfort working in a dynamic, data- oriented team with several ongoing concurrent projects.
• Professional certifications in data science

PREFERRED QUALIFICATIONS

• Master’s degree in stats, applied math, or related discipline.
• Experience with No SQL, Pig, Hive, and PySpark , Big Query.