Senior Data Scientist

Reposted 14 Days Ago
Be an Early Applicant
Riyadh, SAU
Hybrid
Senior level
Artificial Intelligence • Big Data • Business Intelligence
Empowering Businesses with AI-driven Insights and Solutions
The Role
Lead design and delivery of scalable AI/ML solutions: architect and implement distributed, GPU-accelerated models, run end-to-end projects beyond POC, collaborate with stakeholders, present results, and support platform optimization across multiple concurrent projects.
Summary Generated by Built In

Job description

a Data Scientist role, who will be responsible for guiding the successful delivery of Analytic Solutions to internal customers. The Data Scientist will be responsible for designing and executing processes related to AI, ML, predictive / analytical modeling, data mining, and research on large scale, complex data sets, using statistical, machine learning, graph modeling, text mining and other modern techniques. This individual is also responsible for collaborating with various teams and providing periodic updates through presentations and prototype demonstrations. The role will require working on multiple projects simultaneously. This position will also be involved in the formulation of key business requirements to be solved, rationalizing the various analytical approaches to solve those problems. Finally, this position is involved in helping to develop, analyze and draw conclusions, and presenting the results back to business users.

Key responsibilities

Must know the in and out of the AI/ML algorithm being used and not just the library to call.

Should have commissioned at least two projects end to end beyond the Proof of Concept.

Design state of the art descriptive, diagnostic and predictive algorithms based on the business
Requirements

  • Deliver enterprise level analytics solutions to SLB customers
  • Provide analytics solutions in Big data platform which can scale
  • Design distributed, GPU and parallelized algorithms
  • Architect the data science solutions to complex high dimensional data
  • Deep dive on to theoretical and implementation details and provide the solution fundamentals
  • Support architecture and platform team to optimize their operation
  • Capable to train and gain expertise quickly on new Infrastructure tools and all assigned technologies
  • Business
  • Engage with the business segments and internal stakeholders to capture requirements
  • Work closely with analysts and business process managers to develop an end-to-end analytics solution
  • Present and Communicate solution design with Business & IT audience
  • External Presence
  • Engage with the external technical and business community to brand and differentiate analytics best practices in
  • Participate in technical forums and other appropriate events and conferences
  • Qualifications and Requirements Essential qualifications
  • PhD or master’s degree in computer science, Electrical Engineering, Mathematics and Computing, Operations Research from top tier institutes.
  • Devops driven 4-6 years of Industrial experience in developing core machine learning algorithms
  • Academically trained in the field of machine learning/AI/Data Science/Computer Vision etc
  • Excellent communication, verbal and written skills
  • Key competencies in data science technologies
  • Strong background in some of these listed areas: Machine learning, time series analysis / sensor processing, AI/Deep Learning, optimization/operations research, text analytics/NLP, Applied Mathematics, Decision Sciences, Computer Vision
  • Building and applying machine learning / predictive modelling in real-world use cases
  • Strong understanding and implementation and solution architecting of predictive / analytical modeling techniques, theories, principles, and practices
  • Strong theoretical foundations in machine learning, optimization, stochastic process, linear algebra etc.
  • Excellent knowledge of data mining / predictive modeling tools such as Python, Spark, Tensorflow, Keras, MLlib etc.
  • Ability in designing distributed and parallelized algorithms
  • Ability in deploying real world solutions in Hive, Spark and other Hadoop Technologies in Cloud and In-premise
  • Capable of delivering on multiple competing priorities with little supervision

    Other skills and abilities
  • Deep understanding of big data platforms such as Azure, Google cloud etc.
  • Ability to abstract model representations and formulate repeatable models
  • Strong ability to work in a fast-paced environment
  • Strong ability to work both autonomously and in a team
  • Strong ability to communicate complex quantitative analysis in a clear, precise, and actionable manner to both technical and non-technical audiences
  • Understanding of Oil and Gas domain is a plus
  • Experience working with, processing and managing large data sets (multi TB scale) is preferred
  • Experience in real-time stream processing is a plus
  • Keep continuously up to date on all assigned technologies

 

Skills Required

  • PhD or Master's degree in Computer Science, Electrical Engineering, Mathematics, Operations Research, or related field
  • 4-6 years of industrial experience developing core machine learning algorithms (DevOps-driven)
  • Proven delivery of at least two end-to-end projects beyond proof of concept
  • Deep theoretical foundations in machine learning, optimization, stochastic processes, and linear algebra
  • Strong background in machine learning, time series/sensor processing, AI/Deep Learning, optimization, NLP, decision sciences, or computer vision
  • Expertise designing distributed, GPU-accelerated and parallelized algorithms
  • Experience building and applying predictive models in real-world use cases
  • Ability to architect predictive/analytical modeling solutions for complex, high-dimensional data
  • Excellent knowledge of data mining and modeling tools such as Python, Spark, TensorFlow, Keras, MLlib
  • Ability to deploy solutions in Hive, Spark and other Hadoop technologies in cloud and on-premise environments
  • Strong communication skills to present technical results to business and IT audiences
  • Capability to train quickly on new infrastructure tools and assigned technologies
  • Ability to manage multiple competing priorities with little supervision
  • Deep understanding of big data platforms such as Azure and Google Cloud
  • Experience processing and managing multi-TB scale datasets
  • Experience with real-time stream processing
  • Understanding of Oil and Gas domain
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The Company
HQ: Dubai
190 Employees
Year Founded: 2015

What We Do

As a leading AI and Data Analytics provider in the MENA region, DataScience Middle East specializes in transforming raw data into actionable insights, enabling governments, financial institutions, and telecommunication companies to drive innovation and achieve meaningful business outcomes. Founded in 2015, our expertise lies in developing cutting-edge AI solutions and fostering a deep mastery of analytics. With a focus on delivering impactful, scalable technologies, we are committed to helping organizations harness the power of data to make informed decisions that shape the future. Our core offerings include: 1. Advanced AI & Machine Learning Solutions: Custom-built to address specific industry challenges. 2. Data Management & Analytics: Enabling organizations to unlock the full potential of their data. 3. Compliance & Regulatory Solutions: Ensuring organizations meet industry standards and regulatory requirements, including data privacy, financial compliance, and AI governance. We help businesses navigate complex regulatory landscapes by implementing secure, transparent, and ethical AI and data management practices. 4. End-to-End Consulting: Tailored advisory services that guide clients through every step of their data transformation journey. At DataScience Middle East, we pride ourselves on driving digital transformation across various industries by providing innovative, reliable, and highly efficient AI-driven solutions. With our dedicated team and strong partner network, we empower our clients to excel in a rapidly evolving technological landscape.

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