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senior data scientist

Ras Al Khaimah Economic Zone (RAKEZ)

<div>
 
 
 JOB PURPOSE
 
 
 
 
 
 
 The Senior Data Scientist leads the development of advanced analytical models and AI/ML systems to power strategic decision-making and automation across RAKEZ. The role is central to building models that support lead scoring, customer retention, churn prediction, lifetime value estimation, and operational optimization.
 
 
 
 
 
 This position will drive cross-functional collaboration with stakeholders in strategy, sales, finance, and operations while mentoring junior team members and advancing the maturity of RAKEZ&rsquo;s data science capabilities.
 
 
 
 
 
 
 CORE RESPONSIBILITIES
 
 
 
 
 
 
 
 Data Integration &amp; Exploratory Analysis:
 
 
 
 
 
 <ul>
 <li>
 Integrate, clean, and prepare data from multiple structured and unstructured sources including CRM, ERP, web analytics, and external datasets.
 </li>
 <li>
 Perform exploratory data analysis (EDA) to uncover trends, correlations, and anomalies.
 </li>
 <li>
 Generate insights and hypotheses to guide feature engineering and model selection.
 </li>
 <li>
 Work with data engineers to ensure data pipelines support model requirements and retraining strategies.
 </li>
 </ul>
 
 
 
 
 
 Feature Engineering &amp; Data Preparation:
 
 
 
 
 
 <ul>
 <li>
 Engineer meaningful features from raw and semi-structured datasets to improve model accuracy and interpretability.
 </li>
 <li>
 Address data quality issues through imputation, outlier handling, normalization, and transformation techniques.
 </li>
 <li>
 Contribute to strategies for data augmentation and enrichment to enhance model input quality and generalizability.
 </li>
 </ul>
 
 
 
 
 
 Model Development &amp; Experimentation:
 
 
 
 
 
 <ul>
 <li>
 Build, evaluate, and refine machine learning and statistical models for use cases such as lead conversion, churn risk, and customer segmentation.
 </li>
 <li>
 Design experiments (e.g., A/B testing) and perform hypothesis testing to validate model impact.
 </li>
 <li>
 Use appropriate modeling techniques (e.g., ensemble learning, regression, classification, clustering) based on business needs.
 </li>
 </ul>
 
 
 
 
 
 Explainability, Validation &amp; Monitoring:
 
 
 
 
 
 <ul>
 <li>
 Generate and communicate explainable AI insights using tools like SHAP and LIME.
 </li>
 <li>
 Conduct rigorous model validation, cross-validation, and post-deployment monitoring.
 </li>
 <li>
 Partner with Data and ML Engineers to integrate monitoring and retraining pipelines.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Communication:
 
 
 
 
 
 <ul>
 <li>
 Translate business objectives into analytical workflows and deliver insights to non-technical stakeholders.
 </li>
 <li>
 Collaborate with data engineers, analysts, and product owners to align on delivery timelines and priorities.
 </li>
 <li>
 Present models and recommendations clearly to leadership and technical teams.
 </li>
 </ul>
 
 
 
 
 
 Research &amp; Continuous Learning:
 
 
 
 
 
 <ul>
 <li>
 Research and implement state-of-the-art techniques and tools in machine learning, deep learning, and artificial intelligence to ensure that systems created are efficient and effective.
 </li>
 <li>
 Stay updated on industry trends, academic research, and emerging AI/ML methodologies.
 </li>
 <li>
 Recommend and implement novel approaches to improve model performance and business outcomes.
 </li>
 </ul>
 
 
 
 
 
 QUALIFICATIONS, EXPERIENCE, &amp; SKILLS
 
 
 
 
 
 
 
 Educational Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Statistics, Computer Science, Applied Mathematics, or related field.
 </li>
 <li>
 PhD is a plus and may substitute for years of work experience.
 </li>
 </ul>
 
 
 
 
 
 Professional Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Deep understanding of machine learning algorithms, statistical modeling, and experimentation design.
 </li>
 <li>
 Proficiency in Python, SQL, and libraries like scikit-learn, XGBoost, TensorFlow, or PyTorch.
 </li>
 <li>
 Familiarity with model interpretability techniques and tools (e.g., SHAP, LIME).
 </li>
 <li>
 Strong experience in source systems such as SAP ERP, Salesforce CRM, SaaS Applications, Google Analytics and structured/unstructured data sources.
 </li>
 </ul>
 
 
 
 
 
 Required Experience:
 
 
 
 
 
 <ul>
 <li>
 7+ years of experience in applied data science, ideally within CRM, finance, or operational use cases.
 </li>
 <li>
 Experience in building production-grade models and partnering with MLOps for deployment.
 </li>
 <li>
 Proven track record of delivering business value from data science initiatives.
 </li>
 </ul>
 
 
 
 
 
 Other requirements:
 
 
 
 
 
 <ul>
 <li>
 Excellent communication skills with both technical and business stakeholders.
 </li>
 <li>
 Passion for solving real-world problems using AI/ML.
 </li>
 <li>
 Experience in agile delivery environments is preferred.
 </li>
 </ul>
 
 
</div>

Senior Data Scientist

Dataiku

The role of a Data Scientist at Dataiku is quite unique. Our Data Scientists not only code up solutions to real-world problems, but also participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, some user training, and co-developing data science projects from design to deployment.
Just as non-technical skills are important, so too are technical skills. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team primarily uses Python and SQL, with occasional work in other languages (e.g., R, PySpark, JavaScript). An ideal candidate is excited to learn complex new technologies and modelling techniques while being able to explain their work to other data scientists and clients.
In this role, you'll help the team:
<ul>
<li>
Co-develop production-level data science projects with our customers
</li>
<li>
Analyse and investigate various kinds of data and machine learning applications across industries and use cases
</li>
<li>
Help users discover and master the Dataiku platform, via user trainings, office hours, and ongoing consultative support
</li>
<li>
Provide data science expertise both to customers and internally to Dataiku s sales and marketing teams
</li>
<li>
Develop custom Python-based plugins in collaboration with Solutions, R&amp;D, and Product teams, to enhance Dataiku s functionality
</li>
</ul>
Technical skills that may help you in the role:
<ul>
<li>
Experience with Consulting and/or Customer-facing Data Science roles
</li>
<li>
Experience with Data Engineering or MLOps
</li>
<li>
Experience developing WebApps in JavaScript, RShiny, or Dash
</li>
<li>
Experience building APIs
</li>
<li>
Experience using enterprise data science tools
</li>
<li>
Passion for teaching or public speaking
</li>
</ul>

Confidential

<div>
 
 We are looking for exceptional talent to join our data team. Currently, we have an exciting opportunity for a Data Scientist. We are seeking individuals with deep expertise in data science, a proactive approach, strong collaboration skills, and a passion for cultivating a positive and forward-thinking work environment.
 
 
 
 
 
 ROLES &amp; RESPONSIBILITIES
 
 
 
 
 
 <ul>
 <li>
 Collaborate with IT and data management teams to ensure the accurate and timely collection of data related to all commercial activities within the airport.
 </li>
 <li>
 Develop and implement sophisticated ETL processes integrating diverse data sources.
 </li>
 <li>
 Design and execute complex data models using statistical and machine learning techniques.
 </li>
 <li>
 Lead analytics projects with Azure Data Lake, Azure Databricks, Data Warehouse, and Power BI.
 </li>
 <li>
 Manage, mentor, and grow a team of data scientists and BI developers.
 </li>
 <li>
 Spearhead the integration of advanced analytics into strategic planning, enhancing forecasting accuracy and market response.
 </li>
 <li>
 Collaborate with business units to translate complex data insights into actionable business strategies.
 </li>
 <li>
 Champion the use of data science in identifying new business opportunities and revenue streams.
 </li>
 <li>
 Act as a bridge between the data analytics team and commercial stakeholders, ensuring that data-driven recommendations are actionable and aligned with business objectives.
 </li>
 <li>
 Explore the use of artificial intelligence (AI) and big data solutions to improve the airport&rsquo;s commercial decision-making processes.
 </li>
 <li>
 Stay updated on the latest trends and developments in data analytics and technology to ensure the airport remains at the forefront of innovation
 </li>
 <li>
 Conduct end-to-end data analysis, modelling, and experimentation using Databricks&rsquo; unified data analytics platform.
 </li>
 <li>
 Apply advanced statistical methods, machine learning, and AI algorithms to solve complex business problems.
 </li>
 <li>
 Build and optimize data science models to support business decisions and operational improvements.
 </li>
 <li>
 Collaborate with data engineers to design and maintain efficient data pipelines, ensuring data quality and integrity.
 </li>
 <li>
 Use Databricks for building scalable, distributed data processing workflows and transforming large datasets for analysis.
 </li>
 <li>
 Optimize workflows for big data applications and automate recurring data tasks.
 </li>
 <li>
 Work closely with data engineering, product, and business teams to translate business requirements into data-driven solutions.
 </li>
 <li>
 Lead discussions on best practices and the integration of Databricks for different teams across the organization.
 </li>
 <li>
 Foster a collaborative environment by sharing insights and promoting data science across departments.
 </li>
 <li>
 Design, develop, and implement machine learning models using Databricks to improve decision-making processes.
 </li>
 <li>
 Leverage Databricks' Machine Learning Runtime for tracking, optimizing, and deploying machine learning models.
 </li>
 <li>
 Ensure scalability and performance of models in production, including real-time scoring and retraining.
 </li>
 </ul>
 
 
 
 
 
 Technical skills required
 
 
 <ul>
 <li>
 Natural Language Processing (NLP) deployment
 </li>
 <li>
 Machine Learning (Azure Databricks)
 </li>
 <li>
 ML experiments and training
 </li>
 <li>
 Deployment of production (MLOps)
 </li>
 <li>
 Take end to end ownership of all ML features
 </li>
 <li>
 Recommendation systems
 </li>
 <li>
 AI Software Engineering
 </li>
 </ul>
 
 
 
 
 
 EDUCATION AND EXPERIENCE
 
 
 
 
 
 <ul>
 <li>
 A minimum of 6 years of experience in data science, with advanced proficiency in SQL, Python/R, Azure Databricks, Azure Datafactory and BI tools such as Power BI
 </li>
 <li>
 Strong fundamental knowledge in machine learning, statistical analysis, and predictive modelling.
 </li>
 <li>
 Proficiency in Databricks and Spark for large-scale data processing.
 </li>
 <li>
 Strong experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and SQL.
 </li>
 <li>
 Expertise in Python, Scala, or R for data science tasks.
 </li>
 <li>
 Experience with cloud platforms ( Azure) and Databricks&rsquo; cloud infrastructure.
 </li>
 <li>
 Excellent problem-solving and analytical thinking.
 </li>
 <li>
 Strong collaboration and communication skills.
 </li>
 </ul>
 
 
</div>

<div>
 Dataiku is The Universal AI Platform&trade;, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents. Providing no-, low-, and full-code capabilities, Dataiku meets teams where they are today, allowing them to begin building with AI using their existing skills and knowledge.
 
 
 The role of a Data Scientist at Dataiku is quite unique. Our Data Scientists not only code up solutions to real-world problems, but also participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, some user training, and co-developing data science projects from design to deployment.
 
 
 Just as non-technical skills are important, so too are technical skills. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team primarily uses Python and SQL, with occasional work in other languages (e.g., R, PySpark, JavaScript). An ideal candidate is excited to learn complex new technologies and modelling techniques while being able to explain their work to other data scientists and clients.
 
 
 
 In This Role, You'll Help The Team
 
 
 
 <ul>
 <li>
 Co-develop production-level data science projects with our customers
 </li>
 <li>
 Analyse and investigate various kinds of data and machine learning applications across industries and use cases
 </li>
 <li>
 Help users discover and master the Dataiku platform, via user trainings, office hours, and ongoing consultative support
 </li>
 <li>
 Provide data science expertise both to customers and internally to Dataiku&rsquo;s sales and marketing teams
 </li>
 <li>
 Develop custom Python-based &ldquo;plugins&rdquo; in collaboration with Solutions, R&amp;D, and Product teams, to enhance Dataiku&rsquo;s functionality
 
 
 </li>
 </ul>
 
 You might be a good fit for the role if you have:
 
 
 
 <ul>
 <li>
 English - fluent, Arabics - fluent/native will be a big plus
 </li>
 <li>
 Curiosity and a desire to learn new topics and skills
 </li>
 <li>
 Empathy for others and an eagerness to share your knowledge and expertise with your colleagues, Dataiku&rsquo;s customers, and the general public
 </li>
 <li>
 The ability to clearly explain complex topics to technical as well as non-technical audiences
 </li>
 <li>
 2 - 10 years of experience with Python and SQL
 </li>
 <li>
 2 - 10 years of experience with building ML models and using ML tools (e.g., sklearn)
 </li>
 <li>
 Familiarity with data visualisation in Python and R
 </li>
 <li>
 Understanding of underlying data systems such as Cloud architectures, Hadoop, or SQL
 
 
 </li>
 </ul>
 
 Technical Skills That May Help You In The Role
 
 
 
 <ul>
 <li>
 Experience with Consulting and/or Customer-facing Data Science roles
 </li>
 <li>
 Experience with Data Engineering or MLOps
 </li>
 <li>
 Experience developing WebApps in JavaScript, RShiny, or Dash
 </li>
 <li>
 Experience building APIs
 </li>
 <li>
 Experience using enterprise data science tools
 </li>
 <li>
 Passion for teaching or public speaking
 
 
 </li>
 </ul>
 
 What are you waiting for!
 
 
 
 At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you&rsquo;d like to learn even more about working here, you can visit our Dataiku LinkedIn page.
 
 
 
 Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at:
 
 reasonable-accommodations@dataiku.com
 
 
 
 Protect yourself from fraudulent recruitment activity
 
 
 
 
 Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.
 
 
 
</div>

Accord Business Group

<div>
<div>
<div>
 Department/Group: PSD
 Reporting to: Solution Development Director
</div>
</div>
 Position Type: full-time
 
</div>
 Essential Duties &amp; Key Responsibilities: 
<ul>
<li>Support the team as they identify business problems and develop an offering vision. Support to include planning, research, and development of POCs.</li>
<li>Collaboratively translate business requirements into functional specifications. Produce appropriate documentation and actively participate in developing technology and workflow solutions.</li>
<li>Able to solve complex data science problems including problem framing, data preparation, model building, model deployment, model management, and output consumption</li>
<li>Strong data management skills for data extraction from relational databases, NoSQL databases, flat files, and data preparation, data quality assessment, and structuring the modeling data mart</li>
<li>Strong fundamentals of applied data science in a business setting</li>
<li>Strong analytical and problem-solving skills required, including a thorough understanding of how to interpret customer business needs and translate them into solution and operational requirements</li>
<li>Hands-on experience building and implementing predictive models using machine learning algorithms R or Python Language</li>
<li>Gathering business requirement and converting to technical design</li>
<li>Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability</li>
<li>Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world</li>
<li>Verifying data quality, and/or ensuring it via data cleaning</li>
<li>Supervising the data acquisition process if more data is needed</li>
<li>Finding available datasets online that could be used for training Defining validation strategies</li>
<li>Defining the pre-processing or feature engineering to be done on a given dataset</li>
<li>Defining data augmentation pipelines</li>
<li>Training models and tuning their hyperparameters</li>
<li>Analyzing the errors of the model and designing strategies to overcome them</li>
<li>Coding and Deploying models to production</li>
<li>Testing the performance of the models</li>
<li>Working with integration team and source systems team for seamless integration of data from source system.</li>
<li>Perform ETL data flow, source-target data mapping and creation of Data Mart, Data Model and staging area for data loading.</li>
<li>Strong customer interaction experience</li>
</ul>
 Job Specifications 
<ul>
<li>7+ yrs. of experience in advanced analytics and predictive modeling (related to Telecom CVM Analytics) and in real-world business experience in a data science role</li>
<li>Ability to understand/translate customer business needs into data requirements and analytical techniques</li>
<li>Support data acquisition, validation, cleaning/preparation, and management from incoming data sources to facilitate analysis. Fluency in SQL is required.</li>
<li>Covering the areas of full Analytics life cycle, from data preparation to advanced analytics predictive modelling, AI and dynamic dashboards for data visualization and ML-Ops</li>
<li>Telecom experience is required at least 4 years</li>
<li>High communication skills, Ability to communicate with and instruct people with various technical backgrounds, think analytically, write and edit technical material, and relate statistical concepts and applications to statistical and non-statistical SAS users</li>
<li>Have excellent programming skills</li>
<li>Have excellent English oral and written skills</li></ul>

Emirates NBD

<div>
 
 
 Organization Unit Purpose
 
 
 
 Emirates NBD is one of the largest banks in the Middle East, with over USD 6Bn in revenues and 14000 employees globally. As part of its strategic mandate, the bank has recently setup its Advanced Analytics Centre of Excellence for driving ENBD&rsquo;s ambitious advanced analytics agenda across ENBD.
 
 
 
 
 
 Core objectives of the center include:
 
 
 - Deliver 500-800 Mn AED business impact through a series of use cases/ AA projects executed in collaboration with the BU&rsquo;s
 
 
 - Instill a data driven culture across ENBD by building organization wide capabilities in advanced analytics
 
 
 
 
 
 The CoE will act as an enabler to the BUs to deploy advanced analytics models to drive smarter decisions across different domains. It will act as a guiding light to BUs to ideate on what&rsquo;s possible with advanced analytics, help them prioritize these ideas, and pilot and productionalize them through cross-functional AA squads.
 
 
 
 
 
 It will house highly skilled data scientists, data engineers and other digital talent that will be an integral part of cross-functional squads that execute AA projects.
 
 
 
 
 
 The AA agenda is a high visibility and high priority initiative for ENBD. AA CoE will be governed at ExCo level, including impact tracking, a ringfenced budget &amp; performance management
 
 
 
 
 
 
 Job Purpose
 
 
 <ul>
 <li>
 The senior data scientist scopes, designs, and implements machine-learning models to support use case execution with a view of achieving overall objectives and targets
 </li>
 <li>
 The role is highly collaborative and works with product owners, business translator, data warehousing and data engineering teams in creating big data applications through the utilization of structured and unstructured data, designing optimal data architecture, and experimenting on new machine learning techniques
 </li>
 <li>
 The senior data scientist is expected to take charge of end to end delivery of machine learning models including regularly testing and maintain analytical models to improve efficiency and keep up with changing business needs
 </li>
 <li>
 The role supports Translators in communicating the design, functioning and output of the analytical models/solutions developed
 </li>
 <li>
 The senior data scientist additionally plays a mentorship role to others in the team, guiding junior colleagues in execution of their duties, and mentoring them in their professional growth
 </li>
 </ul>
 
 
 
 
 
 Job Content
 
 
 
 Deliver a strong roadmap of AA projects in collaboration with Business Units
 
 <ul>
 <li>
 Designs and implement machine-learning models to support the business&rsquo;s numerous initiatives and programs with a view of achieving overall objectives and targets
 </li>
 </ul>
 
 
 Artefact documentation
 
 
 <ul>
 <li>
 Successful documentation of reusable code
 </li>
 </ul>
 
 
 Development and learning
 
 
 <ul>
 <li>
 Achieve personal technical development and learning goals
 </li>
 </ul>
 
 
 Collaboration and knowledge share
 
 
 <ul>
 <li>
 Conduct knowledge sharing sessions internally within the CoE as well as externally in meetups, conferences etc
 </li>
 <li>
 Participates in and helps plan cultural initiatives for CoE
 </li>
 </ul>
 
 
 
 
 
 Education
 
 
 <ul>
 <li>
 University degree
 </li>
 <li>
 Advanced degree (MS/Ph.D) in Computer Applications, Economics, Statistics or Mathematics or related technical discipline with high analytical rigor is desirable
 </li>
 </ul>
 
 
 
 
 
 Experiences
 
 
 
 6-8 years of experience in a data science role is essential
 
 
 
 
 
 
 Knowledge &amp; Skills
 
 
 <ul>
 <li>
 Validated experience of defining analytics road map and leading analytics engagements
 </li>
 <li>
 Should have experience in machine learning, statistics, optimization or related fields
 </li>
 <li>
 Experience with programming is a must; specifically experience in R or Python
 </li>
 <li>
 Experience of working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) is essential
 </li>
 <li>
 Strong analytical and problem-solving skills
 </li>
 <li>
 Worked in agile environments with multiple stakeholders from the business
 </li>
 </ul>
 
 
 
 
 
 Behavioral Competencies
 
 
 <ul>
 <li>
 Practical and action oriented
 </li>
 <li>
 Compelling communicator
 </li>
 <li>
 Excellent stakeholder management
 </li>
 <li>
 Foster and promote entrepreneurial spirit and curiosity amongst team members
 </li>
 <li>
 Team player
 </li>
 <li>
 Quick learner
 </li>
 </ul>
 
 
</div>

Senior Data Scientist - Advanced Analytics CoE

Nabat

<div>
 
 
 Who is Nabat?
 
 
 
 
 
 
 
 Nabat is a climate-tech startup based in the UAE using advanced technology to protect and restore natural ecosystems with precision and scale!
 
 We operate at the intersection of ecological &amp; environmental sciences, GIS, AI, and robotics. Our mission is to enable data-driven, science-backed ecosystem management and restoration at the speed and scale necessary to address the critical challenges of climate change, deforestation, land erosion, and biodiversity loss. Our comprehensive solution - consisting of ecosystem management software, precision aerial seeding drones, AI &amp; ecological models, and restoration services - is already being used to plant millions of mangroves in the UAE. But we&rsquo;re just getting started, as we build our platform to serve the needs of coastal, marine and arid ecosystems around the world.
 
 
 
 
 
 If this mission resonates with you, let&rsquo;s talk.
 
 
 
 
 
 🔹
 
 What is the role?
 
 
 
 
 
 
 We&rsquo;re building our product development team from the ground up and are looking for highly talented, self-driven
 
 Senior Data Scientists with proven experience using cutting-edge data science techniques to extract science-backed insights from large, complex geospatial data sets
 
 .
 
 
 
 
 
 📍
 
 Relocation to the UAE is required
 
 &ndash; generous relocation benefits and visa sponsorship (for the employee and their family) will be provided.
 
 
 
 
 
 
 🔹 Your responsibilities will include:
 
 
 
 
 
 
 &bull;
 
 Act as senior/staff-level individual contributor
 
 to own the development of analytical and predictive models for Nabat&rsquo;s AI-powered ecosystem management platform, using a variety of AI/ML and statistical techniques.
 
 
 &bull;
 
 Research, develop, train, validate, refine and deploy models
 
 that use deep domain knowledge to extract user-friendly scientific and ecological insights from geospatial data.
 
 
 Some of the problems you might be working on using satellite and drone imagery:
 
 
 &EmptyVerySmallSquare;️ land use/cover classification
 
 
 &EmptyVerySmallSquare;️ identification of plant native and invasive species
 
 
 &EmptyVerySmallSquare;️ estimating carbon stock and biodiversity
 
 
 &EmptyVerySmallSquare;️ modeling and predicting the outcome of different restoration scenarios
 
 
 &EmptyVerySmallSquare;️ creating optimal flight paths for multi-drone seeding operations
 
 
 &EmptyVerySmallSquare;️ detecting ecosystems at risk
 
 
 &EmptyVerySmallSquare;️ measuring plant-level growth metrics
 
 
 &EmptyVerySmallSquare;️ high-throughput phenotyping, and so on.
 
 
 &bull; In close collaboration with software and data engineers,
 
 design and implement well-architected, scalable, robust, high-performance, AI/ML-powered systems
 
 for ingestion, storage, processing, analysis, insight extraction, and visualization of large amounts of geospatial time-series data (geotagged, ultra-high-resolution RGB, multi- and hyper-spectral imagery, KML files, LIDAR point clouds, etc from satellites and drones).
 
 
 &bull;
 
 Communicate and collaborate cross-functionally
 
 with product managers, software, hardware and data engineers, ecologists, GIS data analysts, drone pilots, operations folks, and end users to deliver key initiatives.
 
 
 &bull;
 
 Knowledge transfer from and continuous engagement with researchers
 
 (from Technology Innovation Institute) and external partners to understand and take ownership of what has been built to date, become the subject matter expert for your product domain, and lead the research &amp; development roadmap for your domain.
 
 
 
 
 
 
 🔹 What are we looking for?
 
 
 
 
 
 
 &bull;
 
 A strong research/academic foundation
 
 with at least a Master's degree in engineering, data science, mathematics, ecological or environmental science, or similar fields, and ideally published research in peer-reviewed journals.
 
 
 &bull;
 
 Extensive, hands-on development experience with AI/ML model development in the geospatial, computer vision and/or remote sensing domain
 
 , including:
 
 
 &EmptyVerySmallSquare;️ Familiarity with the latest machine learning techniques and models for image analysis, object detection, semantic segmentation, pattern recognition, predicting outcomes, anomaly detection, or similar using large geospatial datasets (RGB, multi- and hyper-spectral drone imagery, LIDAR point clouds, satellite imagery, etc)
 
 
 &EmptyVerySmallSquare;️ Experience combining data from multiple sources (sensor fusion) such as drones, satellites, ground truth, in-field sensors or from multiple models (ensemble methods) to improve performance
 
 
 &EmptyVerySmallSquare;️ Researching appropriate models and techniques given a problem space, scientific and business context, and validating different options before recommending a solution
 
 
 &EmptyVerySmallSquare;️ Experience using supervised and unsupervised learning, deep learning, CNNs, RNNs, GANs, and the like in the geospatial domain
 
 
 &EmptyVerySmallSquare;️ Determining quantifiable measures for the quality of data and performance of models, evaluating and communicating these metrics to stakeholders
 
 
 &EmptyVerySmallSquare;️ Using geospatial data processing, analysis, and visualization tools (Python, R, PyTorch, Jupyter, QGIS, Grass GIS, ArcGIS, etc)
 
 
 &EmptyVerySmallSquare;️ Experience performing self-directed exploratory data analysis using statistical and visualization tools to understand patterns, trends, and anomalies and present results
 
 
 &EmptyVerySmallSquare;️ Experience working with and deploying production-ready models to cloud platforms: AWS, GCP, or Azure
 
 
 &EmptyVerySmallSquare;️ Experience working with software engineers, data engineers and GIS data analysts to productize and launch models to production
 
 
 &bull;
 
 Builder/entrepreneur mindset
 
 : You've created something meaningful from the ground up - whether leading a project, founding a venture, or crafting an impressive side project that demonstrates your initiative.
 
 
 &bull;
 
 Communication excellence
 
 : You articulate ideas clearly and document thoroughly, understanding that transparent communication is fundamental to our collaborative approach.
 
 
 &bull;
 
 Bias for action and execution
 
 : You move with purpose and velocity, driving for impact rather than perfection. You're comfortable making decisions and failing fast when necessary to achieve results. You prioritize shipping and iterating over endless conceptualizing.
 
 
 &bull;
 
 Problem-solving aptitude
 
 : You approach challenges with creativity and pragmatism, finding elegant solutions that balance technical constraints with user needs.
 
 
 &bull; Nice to haves: Previous experience building products in the domain of geospatial AI, remote sensing, earth observation, environmental monitoring, precision agriculture, or drone robotics.
 
 
 
 
 
 
 🔹Why join Nabat?
 
 
 
 
 
 
 A once-in-a-lifetime opportunity to
 
 
 
 
 <ul>
 <li>
 
 Join a well-funded early-stage tech startup
 
 at the intersection of some of the most exciting, disruptive and innovative technologies in the world - geospatial AI, remote sensing, drone robotics, ecology &amp; agricultural science.
 </li>
 <li>
 
 Design, build and shape a product from the ground up
 
 using your unique skills and expertise .
 </li>
 <li>
 
 Work with a truly international and world-class R&amp;D team
 
 both within Nabat and in collaboration with 1200+ researchers, scientists and technologists in the larger Advanced Technology Research Council (
 
 https://www.atrc.gov.ae/
 
 ), Technology Innovation Institute (
 
 https://www.tii.ae/
 
 ), and VentureOne (
 
 https://www.ventureone.ae/
 
 ) ecosystem.
 </li>
 <li>
 
 Relocate to Abu Dhabi &ndash; one of the safest, most livable, expat-friendly cities in the world
 
 - with an &ldquo;all inclusive&rdquo; relocation package for you and your family, that includes work &amp; residence visa sponsorship, business class flights, orientation tour, school and house search, and luxury hotel stay until you find your new home.
 </li>
 <li>
 
 Make a real and direct impact
 
 to solving the most critical challenges of our time &ndash; climate change and ecosystem loss!
 </li>
 </ul>
 
 
 
 
 
 🔹What is the hiring process like?
 
 
 
 
 
 
 We believe in making your hiring and onboarding seamless and transparent. Here is what to expect from us:
 
 
 
 
 <ul>
 <li>
 
 Initial screening call
 
 with a member of our Talent team to ensure expectations and experience aligns.
 </li>
 <li>
 
 First interview with hiring manager
 
 about the role and ask questions &ndash;
 
 Taha Ghaznavi
 
 , Chief Product Officer, Nabat.
 </li>
 <li>
 
 Second interview with technical team member(s)
 
 to assess your capabilities. Might include a coding test and/or small case study.
 </li>
 <li>
 
 Third interview with a senior leader
 
 to assess culture fit and give you opportunity to meet your future stakeholders.
 </li>
 <li>
 Hiring decision and conditional offer.
 </li>
 <li>
 Background check and final offer.
 </li>
 <li>
 Relocation to the UAE and onboarding!
 </li>
 </ul>
 
 
 
 
 Apply with your CV and tell us what makes you &amp; your experience a great fit for Nabat.
 
</div>

Senior Data Scientist (Geospatial AI)

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