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senior 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>

Senior Data Scientist

<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>

Client of Involved Solutions

About the role <ul> <li>Build, test, and deploy predictive and machine learning models for fintech use cases.</li> <li>Work with large-scale transactional and customer datasets to deliver actionable insights.</li> <li>Lead experimentation and A/B testing to optimise products and user journeys.</li> <li>Partner with engineering teams to scale models into production and monitor performance.</li> </ul>

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>

Careem

<div><div>Careem is building the Everything App for the greater Middle East &mdash; making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people&rsquo;s lives and build an awesome organisation that inspires. 
Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region&rsquo;s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.

We&rsquo;re now entering our next chapter &mdash; one powered by AI. We&rsquo;re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it&rsquo;s streamlining operations, enhancing customer experience, or reimagining internal systems &mdash; we want people who can make Careem work smarter and move faster.</div><div>
About the team

The Careem Data Science team&rsquo;s mission is to drive competitive value from data at scale through building AI models to optimize user experiences, decision-making, operational efficiencies, and lead the region&rsquo;s AI ecosystem. As one of the tech leaders in this team, you will be at the forefront of fulfilling this mission. You will be working with the top data science talent of the region, while innovating on our user experience using GenAI.

What you'll do
<ul>
<li>Be part of a 0-1 AI transformation for the Careem app from a personalization perspective.</li>
<li>Build a long-term vision on how we can rethink our customer acquisition and engagement strategies, leveraging data in our decision-making.</li>
<li>Drive exploratory analysis to understand the ecosystem, user behaviour, and identify new levers to help move metrics and build models of user behaviours for analysis and product enhancements.</li>
<li>Shape and influence data/ML models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products.</li>
<li>Provide product leadership by sharing data-based recommendations to communicate the state of the business, the root cause of change in metrics, and experimentation results, influencing product and business decisions</li>
<li>Implement scalable machine learning algorithms that will be used in production on big data.</li>
<li>Embark on exploratory data analysis projects to achieve a better understanding of phenomena as well as to discover untapped areas of growth and optimization.</li>
<li>Answer complex analytic questions from big data sets to help Careem shape its products and services in a better way.</li>
<li>Help define and track the appropriate key metrics for specific projects.</li>
<li>Design and run randomized controlled experiments, analyze the resulting data, and communicate results with other teams.</li>
<li>You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices.</li>
<li>Build and deploy retrieval augmented generation systems and other applications of large language models.</li>
</ul>
What you'll need
<ul>
<li>6 - 8 years of experience in data mining, predictive modelling, time series analysis, machine learning, Big Data methodologies, and transformation and cleaning of both structured and unstructured data.</li>
<li>Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.</li>
<li>Solid experience with Deep Learning Techniques (e.g, attention, retrieval models, etc)</li>
<li>1-2 years of industrial experience in personalization, recommendation or search is a MUST. Preferably working in a product-driven company.</li>
<li>Strong problem-solving and coding skills.</li>
<li>Solid knowledge of AB testing, classic ML, and DL</li>
<li>Solid understanding of recommendations, ranking, and retrieval.</li>
<li>Proficiency and demonstrated experience in: Python, SQL, Spark, Hive.</li>
<li>Demonstrated experience with database technologies (e.g. , Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).</li>
<li>Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik) along with geospatial data processing skill, is a plus.</li></ul></div></div>

Senior Data Scientist II

careem

The Careem Data Science team s mission is to drive competitive value from data at scale through building AI models to optimize user experiences, decision-making, operational efficiencies, and lead the region s AI ecosystem. As one of the tech leaders in this team, you will be at the forefront of fulfilling this mission. You will be working with the top data science talent of the region, while innovating on our user experience using GenAI./p&gt;
 strong&gt;What you'll do/strong&gt; 
<ul>
<li>Be part of a 0-1 AI transformation for the Careem app from a personalization perspective.</li>
<li>Build a long-term vision on how we can rethink our customer acquisition and engagement strategies, leveraging data in our decision-making.</li>
<li>Drive exploratory analysis to understand the ecosystem, user behaviour, and identify new levers to help move metrics and build models of user behaviours for analysis and product enhancements.</li>
<li>Shape and influence data/ML models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products.</li>
<li>Provide product leadership by sharing data-based recommendations to communicate the state of the business, the root cause of change in metrics, and experimentation results, influencing product and business decisions</li>
<li>Implement scalable machine learning algorithms that will be used in production on big data.</li>
<li>Embark on exploratory data analysis projects to achieve a better understanding of phenomena as well as to discover untapped areas of growth and optimization. </li>
<li>Answer complex analytic questions from big data sets to help Careem shape its products and services in a better way.</li>
<li>Help define and track the appropriate key metrics for specific projects. </li>
<li>Design and run randomized controlled experiments, analyze the resulting data, and communicate results with other teams.</li>
<li>You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices.</li>
<li>Build and deploy retrieval augmented generation systems and other applications of large language models.</li>
</ul>
 strong&gt;What you'll need/strong&gt; 
<ul>
<li>6 - 8 years of experience in data mining, predictive modelling, time series analysis, machine learning, Big Data methodologies, and transformation and cleaning of both structured and unstructured data.</li>
<li>Solid experience with Deep Learning Techniques (e.g, attention, retrieval models, etc)</li>
<li>Strong problem-solving and coding skills.</li>
<li>Solid knowledge of AB testing, classic ML, and DL</li>
<li>Solid understanding of recommendations, ranking, and retrieval. </li>
<li>Proficiency and demonstrated experience in: Python, SQL, Spark, Hive.</li>
<li>Demonstrated experience with database technologies (e.g. , Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).</li>
</ul>

Splash Software

<div>About the Role
We are seeking a highly motivated Data Scientist with extensive experience in Online Gaming Industry to join our team and drive data-driven decision-making through advanced analytics and machine learning models. The ideal candidate will have a strong technical background, a passion for uncovering insights from complex datasets, and the ability to collaborate with cross-functional teams to solve business challenges.
Key Responsibilities
<ul><li>Design and implement machine learning models to predict trends, detect anomalies, and uncover actionable insights.
</li><li>Analyze structured and unstructured datasets to identify patterns and opportunities for optimization.
</li><li>Develop predictive models and algorithms for key business use cases, such as risk management, forecasting, and segmentation.
 </li><li>Collaborate with data engineers and analysts to ensure data readiness for analysis and model deployment.
 </li><li>Use statistical techniques to validate hypotheses, assess model performance, and improve decision-making processes.
 </li><li>Create and present data-driven insights and recommendations to stakeholders in a clear and compelling manner.
 </li><li>Deploy, monitor, and refine models in production environments to ensure scalability and reliability.
 </li><li>Stay updated on the latest advancements in data science and machine learning, incorporating best practices into projects.
</li></ul>Qualifications
<ul><li>Masters degree in Mathematics or Statistics.
</li><li>Proven experience as a Senior Data Scientist, with expertise in building and deploying machine learning models.
</li><li>Proficiency in Python or R, with experience in data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
 </li><li>Strong knowledge of statistical methods, data modeling, and hypothesis testing.
</li><li>Experience working with large-scale data in environments such as Elasticsearch or SQL databases.
</li><li>Familiarity with data visualization tools (e.g., Kibana, Tableau, or Matplotlib) for presenting insights.
 </li><li>Excellent problem-solving and analytical skills with attention to detail.
</li><li> Strong communication skills, with the ability to translate complex data findings into actionable insights for non-technical stakeholders.
</li><li>Experience in the Online Gaming Industry is a Must.
</li></ul>Preferred Skills
<ul><li>Hands-on experience with anomaly detection and forecasting models.
</li><li>Knowledge of big data tools and frameworks (e.g., Hadoop, Spark).
</li><li> Familiarity with MLOps practices and tools for deploying and managing machine learning models in production.
 </li><li>Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for data science workflows.
 </li><li>Understanding of Elasticsearchs machine learning capabilities is a plus.</li></ul></div>

Data Scientist- Online Gaming Experience

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Data Scientist- Online Gaming Experience