business analyst

data analyst - metal & mining industry content Jobs in Islamabad

data analyst - metal & mining industry content

data operations associate Jobs in Islamabad

data operations associate

senior data scientist

ai/ml engineer

data scientist

Fusemachines

<div>
 
 About Fusemachines
 
 
 
 Fusemachines is a 10+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.
 
 
 
 About the Role:
 
 
 
 
 Location:
 
 Remote | Contractual Full-time
 
 
 We are seeking a Data Scientist with hands-on Python experience and proven abilities to support software activities in an Agile software development lifecycle. We are seeking a well-rounded developer to lead a cloud-based big data application using a variety of technologies. The ideal candidate will possess strong technical, analytical, and interpersonal skills. In addition, the candidate will lead developers on the team to achieve architecture and design objectives as agreed with stakeholders.
 
 
 
 Role Description
 
 
 
 <ul>
 <li>
 Work with developers on the team to meet product deliverables
 </li>
 <li>
 Work independently and collaboratively on a multi-disciplined project team in an Agile development environment
 </li>
 <li>
 Contribute detailed design and architectural discussions as well as customer requirements sessions to support the implementation of code and procedures for our big data product
 </li>
 <li>
 Design and develop clear and maintainable code with automated open-source test functions
 </li>
 <li>
 Ability to identify areas of code/design optimization and implementation
 </li>
 <li>
 Learn and integrate with a variety of systems, APIs, and platforms
 </li>
 <li>
 Interact with a multi-disciplined team to clarify, analyze, and assess requirements
 </li>
 <li>
 Be actively involved in design, development, and testing activities in big data applications
 
 
 </li>
 </ul>
 
 Key Responsibilities
 
 
 
 
 Data Engineering &amp; Processing:
 
 
 
 <ul>
 <li>
 Develop scalable data pipelines using PySpark for processing large datasets
 </li>
 <li>
 Work extensively in Databricks for collaborative data science workflows and model deployment
 </li>
 <li>
 Handle messy, unstructured, and semi-structured data, performing thorough Exploratory Data Analysis (EDA)
 </li>
 <li>
 Apply appropriate statistical measures and hypothesis testing to derive insights and validate assumptions
 
 
 </li>
 </ul>
 
 Data Analysis &amp; Modeling:
 
 
 
 <ul>
 <li>
 Write complex SQL queries for data extraction, transformation, and analysis
 </li>
 <li>
 Build and validate predictive models using techniques such as: Gradient Boosting Machines (GBMs) (e.g., XGBoost, LightGBM), Generalized Linear Models (GLMs) (e.g., logistic regression, Poisson regression)
 </li>
 <li>
 Apply unsupervised learning techniques like clustering (K-Means, DBSCAN), PCA, and anomaly detection
 
 
 </li>
 </ul>
 
 Automation &amp; Optimization:
 
 
 
 <ul>
 <li>
 Automate data workflows and model training pipelines using scheduling tools (e.g., Airflow, Databricks Jobs)
 </li>
 <li>
 Optimize model performance and data processing efficiency
 
 
 </li>
 </ul>
 
 Cloud &amp; Deployment:
 
 
 
 <ul>
 <li>
 Basic experience with Azure or other cloud platforms (AWS, GCP) for data storage, compute, and model deployment
 </li>
 <li>
 Familiarity with cloud-native tools like Azure Data Lake, Azure ML, or equivalent
 
 
 </li>
 </ul>
 
 Required Skills:
 
 
 
 <ul>
 <li>
 Programming Languages: Python (with PySpark), SQL
 </li>
 <li>
 Tools &amp; Platforms: Databricks, Azure (or other cloud platforms), Git
 </li>
 <li>
 Libraries &amp; Frameworks: scikit-learn, pandas, numpy, matplotlib/seaborn, XGBoost/LightGBM
 </li>
 <li>
 Statistical Knowledge: Hypothesis testing, confidence intervals, correlation analysis
 </li>
 <li>
 Machine Learning: Supervised and Unsupervised learning, model evaluation metrics
 </li>
 <li>
 Data Handling: EDA, feature engineering, dealing with missing/outlier data
 </li>
 <li>
 Automation: Experience with job scheduling and pipeline automation
 
 
 </li>
 </ul>
 
 Required Experience:
 
 
 
 <ul>
 <li>
 Minimum 5+ years in Data Science or related fields
 </li>
 <li>
 Hands on experience with Databricks
 </li>
 <li>
 Experience with data cleansing, transformation, and validation
 </li>
 <li>
 Proven technical leadership on prior development projects
 </li>
 <li>
 Hands-on experience with versioning tools such as GitHub, Azure Devops, Bitbucket, etc
 </li>
 <li>
 Hands-on experience building pipelines in GitHub (or Azure Devops, etc.)
 </li>
 <li>
 Hands-on experience using Relational Databases, such as Oracle, SQL Server, MySQL, Postgres or similar
 </li>
 <li>
 Experience using Markdown to document code in repositories or automated documentation tools like PyDoc
 </li>
 <li>
 Strong written and verbal communication skills
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Experience with data visualization tools such as Power BI or Tableau
 </li>
 <li>
 Experience with MLOps, DEVOPS CI/CD tools and automation processes (e.g., Azure DevOPS, GitHub, BitBucket)
 </li>
 <li>
 Containers and their environments (Docker, Podman, Docker-Compose, Kubernetes, Minikube, Kind, etc.)
 </li>
 <li>
 Experience working in cross-functional teams and communicating insights to stakeholders
 
 
 </li>
 </ul>
 
 Education
 
 
 
 Master of Science/B. Tech degree from an accredited university
 
 
 
 Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
 
 
 
 Powered by JazzHR
 
 
 FUhGzfIk9P
</div>

Data Scientist

10Pearls

<div>
 
 Company Overview
 
 
 
 10Pearls is an end-to-end digital technology services partner helping businesses utilize technology as a competitive advantage. We help our customers digitalize their existing business, build innovative new products, and augment their existing teams with high-performance team members. Our broad expertise in product management, user experience/design, cloud architecture, software development, data insights and intelligence, cybersecurity, emerging tech, and quality assurance ensures that we are delivering solutions that address business needs. 10Pearls is proud to have a diverse clientele including large enterprises, SMBs, and high-growth startups. We work with clients across industries, including healthcare/life sciences, education, energy, communications/media, financial services, and hi-tech. Our many long-term, successful partnerships are built upon trust, integrity, and successful delivery and execution.
 
 
 
 Role
 
 
 
 As a Principal/Staff Data Scientist you will spearhead advanced analytics initiatives, leveraging data-driven insights to optimize exploration, production, and operational efficiency. Your role involves building predictive models, deploying machine learning algorithms, and leading a team to solve complex challenges unique to the industry.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Lead the design and implementation of end-to-end data science projects, from defining business problems to deploying advanced machine learning models at scale.
 </li>
 <li>
 Architect and build predictive models, statistical algorithms, and machine learning systems to solve complex business challenges and enhance decision-making
 </li>
 <li>
 Provide technical leadership and mentorship to junior data scientists, promoting best practices and guiding technical development across the team
 </li>
 <li>
 Innovate new methodologies in machine learning and AI, staying at the forefront of emerging tools, techniques, and industry trends
 </li>
 <li>
 Lead cross-functional teams, ensuring alignment and seamless integration between data science, engineering, and business teams
 </li>
 <li>
 Implement robust data governance, validation, and quality assurance processes to ensure the integrity and reliability of data science outputs
 </li>
 <li>
 Partner with data engineering and IT teams to build scalable, automated data pipelines that support data science initiatives
 </li>
 <li>
 Present complex data insights and machine learning results to non-technical stakeholders, ensuring clarity and business relevance
 </li>
 <li>
 Drive the design and execution of experiments, A/B tests, and statistical analyses to measure and optimize the impact of data-driven decisions.
 </li>
 <li>
 Ensure compliance with regulatory requirements, data security, and governance protocols when building scalable data science solutions.
 </li>
 <li>
 Understand client needs and provide tailored, strategic solutions that align with business objectives
 </li>
 <li>
 Build strong relationships by clearly communicating technical concepts and managing expectations
 </li>
 <li>
 Actively participate in recruiting top technical talent for the team
 </li>
 <li>
 Collaborate with the sales team in presales activities, identifying client needs, providing technical expertise, and crafting data-driven solutions to meet business requirements
 </li>
 <li>
 Define and implement data strategies to support exploration, drilling, and production business goals
 </li>
 <li>
 Oversee data collection, cleaning, and integration from diverse sources (e.g., seismic, production logs, IoT sensors, SCADA systems)
 </li>
 <li>
 Ensure data accuracy, consistency, and security while adhering to industry compliance standards
 </li>
 <li>
 Design and implement advanced machine learning models (e.g., predictive maintenance, reservoir simulations, production optimization)
 </li>
 <li>
 Develop algorithms for seismic data interpretation, reservoir characterization, and well-performance forecasting
 </li>
 <li>
 Optimize workflows using natural language processing (NLP) for unstructured data, such as drilling reports and maintenance logs
 </li>
 <li>
 Conduct exploratory data analysis (EDA) to identify trends, anomalies, and optimization opportunities
 </li>
 <li>
 Utilize geospatial analysis and geostatistical techniques to interpret geological and geophysical data
 </li>
 <li>
 Implement real-time data analytics for drilling, well monitoring, and production enhancement
 </li>
 <li>
 Lead the adoption of cloud-based data platforms (e.g., Azure, AWS, Google Cloud) for scalable computation
 </li>
 <li>
 Drive automation of repetitive tasks using advanced scripting and machine learning pipelines.
 </li>
 <li>
 Mentor junior data scientists and engineers, fostering a culture of innovation and excellence
 </li>
 <li>
 Collaborate with engineers, geophysicists, and reservoir managers to translate business challenges into data science solutions
 </li>
 <li>
 Communicate technical findings to non-technical stakeholders through visualizations and reports
 </li>
 <li>
 Develop optimization models for energy efficiency, cost reduction, and supply chain logistics
 </li>
 <li>
 Enhance drilling accuracy and reduce downtime through predictive analytics for equipment maintenance
 </li>
 <li>
 Implement risk assessment models to improve safety and compliance standards
 </li>
 <li>
 Expertise in Python, R, MATLAB, and SQL for statistical modelling and data analysis
 </li>
 <li>
 Proficient in machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and big data tools (e.g., Hadoop, Spark)
 </li>
 <li>
 Hands-on experience with visualization tools like Power BI, Tableau, or D3.js
 </li>
 <li>
 Familiarity with domain-specific software like Petrel, Schlumberger, or Halliburton&rsquo;s Decision Space.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Advanced degree (master's or PhD) in Data Science, Computer Science, or a related field.
 </li>
 <li>
 7+ years of experience in data science
 </li>
 <li>
 Demonstrated success in leading data-driven projects
 </li>
 <li>
 Deep knowledge of machine learning and statistical modelling
 </li>
 <li>
 Strong programming and data engineering skills.
 </li>
 <li>
 Excellent problem-solving and communication abilities
 </li>
 <li>
 Proven track record of innovation in multiple industries
 
 
 </li>
 </ul>
 Powered by JazzHR
 
 
 rtbrr9EuNl
</div>

Principal/Staff Data Scientist

S&P Global

<div>
 
 About The Role
 
 
 
 
 Grade Level (for internal use):
 
 
 
 10
 
 
 
 Team Overview
 
 
 
 Our Data and AI Engineering Team consists of skilled professionals focused on creating innovative and scalable data solutions. We specialise in cloud technologies, especially
 
 AWS and Snowflake
 
 , and prioritise data security and governance.
 
 Collaboration is key
 
 , as we work closely with
 
 Data Scientists and ML Engineers
 
 to advance impactful data projects. We encourage continuous learning and are actively adopting new technologies like
 
 Generative AI models
 
 and advanced machine learning tools to improve our data platforms and achieve outstanding outcomes.
 
 
 
 Role Impact
 
 
 
 In this role, you will design and implement scalable data architectures aligned with strategic goals, especially those supporting all stages of the
 
 Machine Learning (ML) and Generative AI (GenAI) lifecycle
 
 . You will apply your expertise in Snowflake, Python, and cloud technologies to maintain strong data security and integrity. Your work will
 
 drive innovation by developing, optimising, and maintaining production-level data pipelines
 
 that support both analytical and predictive modelling, enhancing data processing efficiency and enabling
 
 data-driven decision-making
 
 across the organisation.
 
 
 Main Contributions
 
 
 
 Responsibilities: (Dual Emphasis on Data Engineering &amp; Data Science Enablement)
 
 
 
 <ul>
 <li>
 ML Data Pipeline Development: Create and uphold scalable, reliable, and secure data infrastructure essential for Machine Learning model training, validation, and inference in production settings.
 </li>
 <li>
 Feature Store Collaboration: Partner with Data Scientists to design, build, and maintain a centralized Feature Store, ensuring consistency, reusability, and low-latency access to features for model training and deployment.
 </li>
 <li>
 GenAI Data Handling: Develop and execute data ingestion and processing workflows for text and unstructured data, including methods for vectorisation and populating vector databases to support Retrieval-Augmented Generation (RAG) architectures.
 </li>
 <li>
 Core Data Engineering: Build and maintain robust ELT/ETL processes within Snowflake and AWS to integrate diverse, large-scale data sources, ensuring excellent data governance, quality, and performance for general business intelligence.
 </li>
 <li>
 MLOps Partnership: Collaborate closely with ML Engineers to operationalise data flows to and from MLOps platforms (e.g., SageMaker, MLflow), focusing on automating pipelines and managing data versioning.
 </li>
 <li>
 Query and Compute Efficiency: Optimize data storage and computing resources across the platform to speed up data science experiments and model training workloads, while managing costs effectively.
 </li>
 <li>
 Data Security and Compliance: Implement advanced security measures to safeguard sensitive data used in AI datasets, maintaining data integrity and confidentiality in line with governance standards.
 
 
 </li>
 </ul>
 
 Required Skills And Experience
 
 
 
 
 Essential Skills: (Dual Focus)
 
 
 
 <ul>
 <li>
 Data Engineering Expertise (5+ Years): Extensive experience in a core Data Engineering role, including 5+ years working with Snowflake and strong skills in SQL and Python for data manipulation and engineering.
 </li>
 <li>
 Data Science Enablement: Demonstrated experience building and optimizing data pipelines specifically for Machine Learning model training and deployment (e.g., feature engineering, time-series data handling, complex schema management).
 </li>
 <li>
 Cloud Computing: Solid practical experience with AWS services (S3, Lambda, EC2, ECS) for creating reliable, scalable cloud data solutions.
 </li>
 <li>
 Distributed Processing: Familiarity with distributed computing frameworks such as PySpark or Dask for large-scale data transformation.
 </li>
 <li>
 Data Security: Strong knowledge of RBAC security models and secure data connection protocols.
 </li>
 <li>
 Communication: Excellent communication and teamwork skills, with a proven history of effective collaboration with Data Science and Business teams.
 
 
 </li>
 </ul>
 
 Preferred Qualifications: (AI/ML Specialization)
 
 
 
 <ul>
 <li>
 MLOps / MLOps Platforms: Hands-on experience integrating data systems with MLOps platforms (e.g., MLflow, Amazon SageMaker) for production model deployment.
 </li>
 <li>
 Generative AI Data: Experience with vector databases (e.g., Pinecone, ChromaDB) and familiarity with data preparation for LLMs and RAG architectures.
 </li>
 <li>
 Feature Store Expertise: Practical or theoretical knowledge of Feature Stores (e.g., Feast, Tecton) and their role in the ML lifecycle.
 </li>
 <li>
 Advanced Data Orchestration: Experience with modern orchestrators like Apache Airflow, Prefect, or Dagster for managing complex, data-science-focused workflows.
 </li>
 <li>
 Experience with Cortex AI or comparable cloud AI tools.
 </li>
 <li>
 Certifications in Snowflake, AWS Data Analytics, or related areas.
 
 
 </li>
 </ul>
 #
 
 
 
 What&rsquo;s In It For
 
 
 You?
 
 
 
 
 Our Purpose
 
 
 
 Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology&ndash;the right combination can unlock possibility and change the world.
 
 
 Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&amp;P Global we transform data into Essential Intelligence&reg;, pinpointing risks and opening possibilities. We Accelerate Progress.
 
 
 
 Our People
 
 
 
 We're more than 35,000 strong worldwide&mdash;so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.
 
 
 From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We&rsquo;re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We&rsquo;re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference.
 
 
 
 Our Values
 
 
 
 
 Integrity, Discovery, Partnership
 
 
 
 At S&amp;P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of
 
 integrity
 
 in all we do, bring a spirit of
 
 discovery
 
 to our work, and collaborate in close
 
 partnership
 
 with each other and our customers to achieve shared goals.
 
 
 
 Benefits
 
 
 
 We take care of you, so you can take care of business. We care about our people. That&rsquo;s why we provide everything you&mdash;and your career&mdash;need to thrive at S&amp;P Global.
 
 
 
 Our Benefits Include
 
 
 
 <ul>
 <li>
 Health &amp; Wellness: Health care coverage designed for the mind and body.
 </li>
 <li>
 Flexible Downtime: Generous time off helps keep you energized for your time on.
 </li>
 <li>
 Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
 </li>
 <li>
 Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
 </li>
 <li>
 Family Friendly Perks: It&rsquo;s not just about you. S&amp;P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
 </li>
 <li>
 Beyond the Basics: From retail discounts to referral incentive awards&mdash;small perks can make a big difference.
 
 
 </li>
 </ul>
 For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
 
 
 
 Global Hiring And Opportunity At S&amp;P Global
 
 
 
 At S&amp;P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.
 
 
 
 Recruitment Fraud Alert
 
 
 
 If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&amp;P Global never requires any candidate to pay money for job applications, interviews, offer letters, &ldquo;pre-employment training&rdquo; or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.
 
 
 
 Equal Opportunity Employer
 
 
 
 S&amp;P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
 
 
 If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
 
 
 
 US Candidates Only:
 
 The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf
 
 
 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.1 - Middle Professional Tier I (EEO Job Group), SWP Priority &ndash; Ratings - (Strategic Workforce Planning)
 
 
 
 Job ID:
 
 318971
 
 
 
 Posted On:
 
 2025-08-27
 
 
 
 Location:
 
 Islamabad, Pakistan
 
 
</div>

Senior Data Scientist

About the Role: 
Grade Level (for internal use): 10 Team Overview
 Our Data and AI Engineering Team consists of skilled professionals focused on creating innovative and scalable data solutions. We specialise in cloud technologies, especially AWS and Snowflake , and prioritise data security and governance. Collaboration is key , as we work closely with Data Scientists and ML Engineers to advance impactful data projects. We encourage continuous learning and are actively adopting new technologies like Generative AI models and advanced machine learning tools to improve our data platforms and achieve outstanding outcomes.
 Role Impact
 In this role, you will design and implement scalable data architectures aligned with strategic goals, especially those supporting all stages of the Machine Learning (ML) and Generative AI (GenAI) lifecycle . You will apply your expertise in Snowflake, Python, and cloud technologies to maintain strong data security and integrity. Your work will drive innovation by developing, optimising, and maintaining production-level data pipelines that support both analytical and predictive modelling, enhancing data processing efficiency and enabling data-driven decision-making across the organisation.
 
Main Contributions
 Responsibilities: (Dual Emphasis on Data Engineering & Data Science Enablement)
 ML Data Pipeline Development: Create and uphold scalable, reliable, and secure data infrastructure essential for Machine Learning model training, validation, and inference in production settings.
 Feature Store Collaboration: Partner with Data Scientists to design, build, and maintain a centralized Feature Store , ensuring consistency, reusability, and low-latency access to features for model training and deployment.
 GenAI Data Handling: Develop and execute data ingestion and processing workflows for text and unstructured data , including methods for vectorisation and populating vector databases to support Retrieval-Augmented Generation (RAG) architectures .
 Core Data Engineering: Build and maintain robust ELT/ETL processes within Snowflake and AWS to integrate diverse, large-scale data sources, ensuring excellent data governance, quality, and performance for general business intelligence.
 MLOps Partnership: Collaborate closely with ML Engineers to operationalise data flows to and from MLOps platforms (e.g., SageMaker, MLflow) , focusing on automating pipelines and managing data versioning .
 Query and Compute Efficiency: Optimize data storage and computing resources across the platform to speed up data science experiments and model training workloads , while managing costs effectively.
 Data Security and Compliance: Implement advanced security measures to safeguard sensitive data used in AI datasets , maintaining data integrity and confidentiality in line with governance standards.
 Required Skills and Experience
 Essential Skills: (Dual Focus)
 
Data Engineering Expertise (5+ Years): Extensive experience in a core Data Engineering role, including 5+ years working with Snowflake and strong skills in SQL and Python for data manipulation and engineering.
 Data Science Enablement: Demonstrated experience building and optimizing data pipelines specifically for Machine Learning model training and deployment (e.g., feature engineering, time-series data handling, complex schema management).
 Cloud Computing: Solid practical experience with AWS services (S3, Lambda, EC2, ECS) for creating reliable, scalable cloud data solutions.
 Distributed Processing: Familiarity with distributed computing frameworks such as PySpark or Dask for large-scale data transformation.
 Data Security: Strong knowledge of RBAC security models and secure data connection protocols.
 Communication: Excellent communication and teamwork skills, with a proven history of effective collaboration with Data Science and Business teams .
 Preferred Qualifications: (AI/ML Specialization)
 
MLOps / MLOps Platforms: Hands-on experience integrating data systems with MLOps platforms (e.g., MLflow, Amazon SageMaker) for production model deployment.
 Generative AI Data: Experience with vector databases (e.g., Pinecone, ChromaDB) and familiarity with data preparation for LLMs and RAG architectures .
 Feature Store Expertise: Practical or theoretical knowledge of Feature Stores (e.g., Feast, Tecton) and their role in the ML lifecycle.
 Advanced Data Orchestration: Experience with modern orchestrators like Apache Airflow, Prefect, or Dagster for managing complex, data-science-focused workflows.
 Experience with Cortex AI or comparable cloud AI tools.
 Certifications in Snowflake, AWS Data Analytics, or related areas.
 
#LI-USA
 
What’s In It For You?
 
Our Purpose: 
Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world.
 
Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress.
 
Our People: 
We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.
 
From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference.
 
Our Values: 
Integrity, Discovery, Partnership
 
At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
 
Benefits: 
We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global.
 
Our benefits include: 
Health & Wellness: Health care coverage designed for the mind and body.
 
Flexible Downtime: Generous time off helps keep you energized for your time on.
 
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
 
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
 
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
 
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.
 For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
 
Global Hiring and Opportunity at S&P Global: 
At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.
 
Recruitment Fraud Alert: 
If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here .
 
-----------------------------------------------------------
 
Equal Opportunity Employer
 S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
 
If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
 
US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf
 
----------------------------------------------------------- 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.1 - Middle Professional Tier I (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning)
 
Job ID: 318971
 Posted On: 2025-08-27
 Location: Islamabad, Pakistan

Edge

<div>
 
 
 At Edge
 
 
 
 We&rsquo;re on a mission to eliminate geographic borders as barriers to full-time employment and fair wages. We&rsquo;re creating a global HR platform ecosystem that seamlessly connects exceptional talent worldwide with North American businesses. By making global hiring easier than local hiring, we provide businesses access to a broader talent pool and accelerate their hiring process. Spread across four continents, we&rsquo;re a global team disrupting how people work together.
 
 
 
 
 
 
 Role Overview
 
 
 
 We are looking for a skilled
 
 Data Engineer
 
 to join our team. The ideal candidate will have strong expertise in designing, building, and maintaining scalable data pipelines and warehouses, ensuring data accuracy, quality, and accessibility across the organization.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain
 
 ETL/ELT pipelines
 
 for efficient data processing.
 </li>
 <li>
 Build and optimize
 
 data models and warehouses
 
 to support analytics and reporting.
 </li>
 <li>
 Implement
 
 data governance and quality frameworks
 
 to ensure reliable insights.
 </li>
 <li>
 Integrate data from various sources (APIs, databases, third-party systems).
 </li>
 <li>
 Collaborate with cross-functional teams (engineering, product, analytics) to enable data-driven decision-making.
 </li>
 </ul>
 
 
 
 
 
 Required Skills
 
 
 <ul>
 <li>
 Proven experience in
 
 ETL/ELT pipeline development
 
 .
 </li>
 <li>
 Strong knowledge of
 
 data modeling and data warehousing
 
 .
 </li>
 <li>
 Proficiency in
 
 BigQuery, SQL, and NoSQL databases
 
 .
 </li>
 <li>
 Experience working with
 
 APIs
 
 for data integration.
 </li>
 <li>
 Strong programming skills in
 
 Python
 
 for data engineering tasks and automation.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills
 
 
 <ul>
 <li>
 Experience with
 
 data governance and data quality frameworks
 
 .
 </li>
 <li>
 Familiarity with cloud-based data platforms and modern data stack tools.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 3+ years of experience as a Data Engineer or in a related role.
 </li>
 <li>
 Strong problem-solving and analytical skills.
 </li>
 </ul>
 
 
 
 
 
 Why Join Edge?
 
 
 
 Edge is at a pivotal growth point, offering you the rare opportunity to shape the future of global employment. Your work will directly impact business growth, enable global opportunities, and transform how people work across borders.
 
 
 We&rsquo;re not just offering a job &mdash; we&rsquo;re inviting you to be part of a revolution.
 
 
 Ready to leave a global footprint and change lives? Edge is where your vision becomes reality.
 
 
 
</div>

Data Engineer

Placentek

<div>
 
 Job Title:
 
 Junior AI/ML Engineer
 
 
 
 Location:
 
 Islamabad (On-site)- I-10.
 
 
 
 Job Type:
 
 Full-time
 
 
 
 About The Role
 
 
 
 Were hiring on behalf of one of our long-term technology clients, a services based company working on advanced AI/ML systems across domains like computer vision, NLP, and LLM-based applications.
 
 
 This is a
 
 full-time, on-site role in Islamabad
 
 , ideal for
 
 fresh graduates or junior professionals
 
 (up to 1 year of experience) who are passionate about launching their careers in AI and working on meaningful real-world projects. Youll work closely with experienced engineers and contribute to scalable AI solutions from day one.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Contribute to the design and implementation of machine learning models.
 </li>
 <li>
 Assist in building data pipelines and performing data preprocessing.
 </li>
 <li>
 Conduct exploratory data analysis (EDA) and feature engineering.
 </li>
 <li>
 Train and evaluate models using standard ML techniques and frameworks.
 </li>
 <li>
 Collaborate on experimentation with libraries like Scikit-learn, PyTorch, or TensorFlow.
 </li>
 <li>
 Support documentation of experiments, findings, and model outcomes.
 </li>
 <li>
 Stay updated on new tools, research papers, and best practices in AI/ML.
 </li>
 <li>
 Work closely with cross-functional teams including software engineers and product managers.
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelors degree in Computer Science, Data Science, Electrical Engineering, or a related technical field.
 </li>
 <li>
 Academic or project-based experience in AI/ML, data science, or computer vision.
 </li>
 <li>
 Familiarity with Python and libraries such as NumPy, Pandas, and Matplotlib.
 </li>
 <li>
 Understanding of core ML concepts: model training, evaluation, bias/variance, overfitting, etc.
 </li>
 <li>
 Willingness to learn quickly and contribute actively in a team environment.
 </li>
 <li>
 Strong verbal and written communication skills.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Hands-on exposure to TensorFlow, PyTorch, or Scikit-learn.
 </li>
 <li>
 Final year project, internship, or coursework in AI/ML, NLP, or LLMs.
 </li>
 <li>
 Familiarity with version control (Git), Jupyter Notebooks, or Google Colab.
 </li>
 <li>
 Participation in open-source, Kaggle, or ML-related challenges is a plus.
 </li>
 <li>
 Based in or near Islamabad for on-site collaboration.
 
 
 
 </li>
 </ul>
 
 What Youll Get
 
 
 
 <ul>
 <li>
 Fast-track probation: Standard 2-month probation often reduced to 1 month based on performance.
 </li>
 <li>
 Timely increments: First salary review right after probation; and bi-annual performance reviews.
 </li>
 <li>
 Quarterly bonuses: A percentage of quarterly earnings are shared with the team as performance bonuses.
 </li>
 <li>
 Subsidized lunch: Fresh, affordable meals available during workdays.
 </li>
 <li>
 Health insurance: Full coverage for the employee and their dependents.
 </li>
 <li>
 Team culture: Regular team dinners, events, and a collaborative, high-performance environment.
 
 </li>
 </ul>
</div>

Junior AI/ML Engineer

GrowthRatio Solutions

Job Title: Data Scraping &amp; Annotation SpecialistCompany: GrowthRise Solutions Job Type: Project-Based (Contract)About the Role: We are looking for an experienced Data Scraping &amp; Data Annotation Specialist to support a project involving a list of 6,000 leads. The role requires strong technical expertise in extracting, cleaning, and annotating data to ensure accuracy and reliability.Key Responsibilities:<ul><li>Perform web scraping to collect and organize data from various online sources.</li><li>Annotate and label data accurately according to project requirements.</li><li>Ensure data quality, consistency, and integrity throughout the process.</li><li>Collaborate with the team to meet deadlines and provide regular progress updates.</li></ul>Requirements:<ul><li>Proven experience in data scraping and annotation.</li><li>Proficiency in tools/languages such as Python, BeautifulSoup, Selenium, or similar frameworks.</li><li>Strong attention to detail and ability to work independently.</li><li>Good communication skills and commitment to deadlines.</li></ul>How to Apply: If you have relevant experience and are confident in your data scraping and annotation skills, please apply with your resume, portfolio, or examples of past work.Job Type: Full-timeWork Location: In person

Data Scraping & Annotation Specialist

Explore 282+ Data scientist in Islamabad this September. Find roles across top companies and apply now to boost your career.

282 data scientist jobs IN Islamabad

Data Scientist

Principal/Staff Data Scientist

Senior Data Scientist

Senior Data Scientist

Data Engineer

Junior AI/ML Engineer

Data Scraping & Annotation Specialist