analyst, insights & analytics Jobs in Islamabad

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Career Development Center COMSATS University Islamabad-Islamabad Campus

<div>
 Tajir is a fast-growing B2B commerce startup transforming Pakistan&rsquo;s retail industry through technology. We build scalable software systems that power thousands of retailers, enabling them to procure inventory seamlessly and operate more efficiently.
 
 
 Tajir is backed by leading global investors including Kleiner Perkins and Y Combinator, and we are focused on building a strong engineering and data team to solve real-world problems at scale.
 
 
 
 We Are Currently Hiring
 
 
 
 Software Engineer (Fresh Graduates &amp; Experienced)
 
 
 Software Engineer Intern (3rd Year Students)
 
 
 Data Scientist (Fresh Graduates &amp; Experienced)
 
 
 Data Scientist Intern (3rd Year Students)
 
 
 Apply at
 
 https://jobs.ashbyhq.com/tajir
 
 
 .
 
</div>

Tajir | Software & Data Roles

Fusemachines

<div>
 
 About Fusemachines
 
 
 
 Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 
 
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 
 
 Type: Remote, Full-time
 
 
 Job Description:
 
 
 This is a role responsible for designing, building, and maintaining the automated testing frameworks and Python SDKs required for data integration, parity verification, and user accessibility in the Industrial IoT / Smart Buildings domain.
 
 
 We are seeking a Senior Data Engineer with strong Python and PySpark skills, and proven implementation of automated Data Quality frameworks and CI/CD pipelines, delivering Data and Analytics products using Agile methodology. The ideal candidate will possess strong technical, analytical, and interpersonal skills.
 
 
 Qualification / Skill Set Requirement:
 
 
 <ul>
 <li>
 5+ years of hands-on data engineering experience with deep expertise in the Azure ecosystem
 </li>
 <li>
 Expert Python skills (building Libraries/SDKs, Py4J)
 </li>
 <li>
 Strong experience with PySpark and DataFrames
 </li>
 <li>
 Experience with Automated Testing frameworks (PyTest, JUnit) for data pipelines
 </li>
 <li>
 Experience with Data Quality tools (Great Expectations, Deequ)
 </li>
 <li>
 Deep understanding of Apache Spark Internals (Catalyst Optimizer, Logical Plans)
 </li>
 <li>
 Experience with Databricks and Delta Lake optimization
 </li>
 <li>
 Solid understanding of SDLC and Agile methodologies with hands-on experience in Azure DevOps, GitHub, CI/CD, and artifact management
 </li>
 <li>
 Skilled in data modeling, data design, and data warehousing solutions on Azure Databricks
 </li>
 <li>
 Knowledge of data governance, and security best practices within Azure (AD, NSG, encryption, compliance)
 </li>
 <li>
 Certifications preferred: Azure Fundamentals, Azure Data Engineer Associate, Databricks Certified Data Engineer Professional and Azure Solutions Architect Expert (nice to have)
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Implement scalable and efficient data solutions on Spark and Flink
 </li>
 <li>
 Develop a Python SDK that wraps core libraries for use in Jupyter Notebooks by data scientist and analyst.
 </li>
 <li>
 Build automated Parity Test Suite: CI/CD pipeline that runs queries against "Golden Datasets" in both Spark and Flink and asserts equality
 </li>
 <li>
 Implement Data Quality (DQ) Rules configuration: Defining thresholds for "Completeness" and "Validity" that can be enforced
 </li>
 <li>
 Manage and optimize Azure and Databricks resources, for performance, reliability, and cost-efficiency
 </li>
 <li>
 Transform, clean, and prepare data using SQL, Python and Java
 </li>
 <li>
 Monitor and fine-tune workloads and pipelines for optimal performance and reliability
 </li>
 <li>
 Maintain CI/CD pipelines
 </li>
 <li>
 Maintain clear documentation of solutions, configurations, and workflows
 </li>
 <li>
 Actively participate in Agile team activities and continuous improvement initiatives
 </li>
 <li>
 Promote and enforce data engineering best practices, including data governance, security, and data quality
 
 
 </li>
 </ul>
 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
 
 
 RXObX8Jt99
</div>

Sr. Databricks Azure Data Engineer

Mercurial Minds (Pvt) Ltd

Job Description &ndash; AI EngineerCompany: Mercurial Minds (Pvt.) Ltd. Location: Islamabad (On-site) Employment Type: Full-time Experience Required: 2&ndash;4 years (AI / Machine Learning / Applied Data Science)Company OverviewMercurial Minds (Pvt.) Ltd. is a forward-thinking technology and digital innovation company delivering end-to-end software solutions that help businesses transform, scale, and innovate through modern digital technologies. Our expertise spans cloud-native platforms, data-driven systems, AI-powered products, and large-scale digital transformation initiatives across telecom, media-tech, and enterprise environments.At Mercurial Minds, we focus on building intelligent, scalable, and production-ready systems that create measurable business value. We foster a culture of innovation, technical excellence, and continuous learning.Role OverviewWe are seeking an experienced and highly motivated AI Engineer to design, build, and deploy intelligent systems powered by modern AI technologies, including large language models (LLMs), machine learning, and advanced data pipelines.This role involves working on end-to-end AI solutions such as agentic systems, retrieval-augmented generation (RAG), semantic search, question-answering systems, summarization engines, recommendation systems, AI-powered matching platforms, and production-grade analytics solutions.The ideal candidate combines strong AI engineering expertise with applied machine learning knowledge and hands-on experience deploying scalable AI solutions in production environments.Key Responsibilities<ul><li>Design, develop, and optimize end-to-end AI-powered applications</li><li>Build and maintain RAG pipelines using vector databases, embeddings, and document processing workflows</li><li>Implement semantic search, filtering, and ranking systems across large and multi-source datasets</li><li>Fine-tune, evaluate, and deploy open-source LLMs and other machine learning models</li><li>Design scalable data pipelines for ingestion, cleaning, transformation, and storage</li><li>Deploy models and AI services using cloud infrastructure and containerization technologies</li><li>Collaborate with product, backend, and frontend teams to integrate AI capabilities into applications</li><li>Monitor model performance, latency, and operational costs, and continuously optimize system quality</li></ul>Required Skills &amp; Qualifications<ul><li>Bachelor&rsquo;s degree (BS) in Computer Science, Artificial Intelligence, Data Science, or a related field</li><li>Strong proficiency in Python programming and software engineering best practices</li><li>Hands-on experience with agentic and LLM frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, or similar</li><li>Experience working with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma, etc.)</li><li>Solid understanding of NLP, embeddings, transformers, and semantic similarity techniques</li><li>Experience deploying models using Docker and cloud platforms (AWS, Azure, or GCP)</li><li>Familiarity with REST APIs and microservices architectures</li><li>Knowledge of data processing libraries (Pandas, NumPy) and machine learning frameworks (Scikit-learn, PyTorch, or TensorFlow)</li><li>Experience with model evaluation, prompt engineering, and performance optimization</li><li>Understanding of the full ML lifecycle including training, validation, deployment, and monitoring</li></ul>Nice to Have<ul><li>Experience fine-tuning open-source models (LoRA, PEFT, quantization)</li><li>Knowledge of MLOps tools such as MLflow, Weights &amp; Biases, Airflow, or Kubeflow</li><li>Background in data science or advanced analytics</li><li>Familiarity with graph databases or knowledge graphs</li><li>Experience building high-availability production systems</li><li>Master&rsquo;s degree (MS) in Computer Science, Artificial Intelligence, Data Science, or related field</li><li>Strong hands-on project experience in real-world AI applications</li></ul>What We Offer<ul><li>Opportunity to work on real-world, high-impact AI solutions</li><li>Exposure to cutting-edge AI and LLM technologies</li><li>Collaborative and fast-growing engineering environment</li><li>Competitive compensation and career growth opportunities</li></ul>Ideal Candidate ProfileYou are someone who enjoys taking AI ideas from concept to production, understands both theoretical foundations and practical implementation of modern AI systems, and actively stays current with rapidly evolving AI and LLM ecosystems.Job Type: Full-timeAbility to commute/relocate:<ul><li>Islamabad: Reliably commute or planning to relocate before starting work (Preferred)</li></ul>Application Question(s):<ul><li>Do you have hands-on experience building or deploying LLM-based applications (e.g., RAG pipelines, semantic search, or agentic systems) in a production or real-world environment?</li></ul><ul><li> Have you worked with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus, Chroma) and deployed AI/ML models using cloud platforms or Docker?</li></ul>Location:<ul><li>Islamabad (Required)</li></ul>Work Location: In person

AI Engineer

Plutus21

<div><h2 class="jobSectionHeader">Job Summary:</h2>
Plutus21 is looking for a Quantitative Researcher to discover, test, and improve systematic alpha signals and portfolio construction for low-frequency equity strategies (typically daily to monthly horizons). This role is designed for exceptional quantitative thinkers coming from Physics, Mathematics, Statistics, Engineering, or other rigorous fields.
Key Responsibilities: 
Research and hypothesis generation:<ul><li>
Translate investment ideas into testable hypotheses with clear metrics and failure criteria</li><li>
Build simple baselines first, then iterate toward stronger models only when justified</li><li>
Data and features (research-grade)</li><li>
Work with panel/time-series equity data and build features with strict as-of availability</li><li>
Implement careful data checks (missingness, outliers, corporate actions, calendar alignment)</li></ul>
Evaluation and robustness:<ul><li>
Design validation protocols appropriate for time series (walk-forward, rolling windows, cross-sectional splits)</li></ul><ul><li>
Detect and prevent common research pitfalls: look-ahead bias, leakage, overfitting, multiple comparisons</li><li>
Perform robustness analysis: turnover, drawdowns, concentration, regime sensitivity, stability across time and cohorts</li><li>
Backtesting and portfolio construction</li><li>
Implement or extend low-frequency backtests for signals and portfolios</li><li>
Model basic frictions realistically (transaction costs, slippage assumptions, liquidity/turnover constraints)</li><li>
Collaborate with engineering/trading to productionize the strongest research findings</li></ul>
Communication and collaboration<ul><li>
Write clear research memos: what you tried, what worked, what didnt, what you recommend next</li><li>
Present results transparently, including uncertainty, limitations, and risk considerations</li></ul>
Qualifications (Core):<ul><li>
Strong quantitative foundation in probability/statistics and at least one of: linear algebra, optimization, numerical methods</li><li>
Ability to design experiments and reason about measurement (baselines, controls, uncertainty, sanity checks)</li><li>
Ability to write working analysis code in Python (preferred) or another language, and communicate code/results clearly</li><li>
Comfort with real-world messy datasets and non-stationary behavior</li><li>
Strong written communication and intellectual honesty (you can say this is inconclusive and explain why)</li><li>
Experience We Value (Any Combination)</li><li>
Prior research experience (academic, industry, independent) demonstrating end-to-end ownership</li><li>
Evidence of strong software fundamentals even without formal CS training: readable code, modularity, reproducibility</li><li>
Work involving time-series or observational data where leakage is a risk (forecasting, causal inference, experiments)</li></ul>
Nice to Have (Not Required):<ul><li>
Any exposure to markets, equities, factor models, or portfolio construction (we can teach this)</li><li>
Familiarity with common research tools: numpy/pandas/scipy/statsmodels/sklearn, Jupyter, Git</li><li>
Experience with simulation/Monte Carlo, Bayesian methods, or causal inference</li></ul></div>

Quantitative Researcher

Nisum

<div>
 We are seeking a Prompt Engineer/Data Analyst to join our team. This hybrid role blends strong data analysis expertise with emerging AI capabilities to optimize Generative AI systems and ensure high data quality for AI-driven initiatives. The ideal candidate is analytical, detail-oriented, and passionate about improving LLM-based solutions to deliver measurable business value.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Design, test, and optimize prompts for various LLM applications (GPT-4, Claude, Llama).
 </li>
 <li>
 Develop reusable prompt templates and implement advanced techniques (few-shot, chain-of-thought, structured prompting).
 </li>
 <li>
 Conduct A/B testing to evaluate and improve prompt performance across different models.
 </li>
 <li>
 Prepare, clean, and validate datasets for fine-tuning and RAG systems.
 </li>
 <li>
 Build and maintain data pipelines to feed structured context into AI systems.
 </li>
 <li>
 Define, track, and report KPIs such as accuracy, latency, and cost efficiency.
 </li>
 <li>
 Develop evaluation frameworks to assess LLM outputs (relevance, factuality, consistency).
 </li>
 <li>
 Create dashboards and reports to communicate AI performance and impact to stakeholders.
 </li>
 <li>
 Maintain prompt libraries, knowledge bases, and documentation for AI systems.
 </li>
 <li>
 Collaborate with cross-functional teams including Engineering, Product, and QA in Agile environments.
 
 
 </li>
 </ul>
 
 What You Know
 
 
 
 <ul>
 <li>
 4+ years of experience as a Data Analyst, Business Analyst, or similar role.
 </li>
 <li>
 Strong proficiency in SQL for data extraction and analysis.
 </li>
 <li>
 Hands-on experience with Python (pandas, numpy) for data manipulation.
 </li>
 <li>
 Experience working with LLM APIs (OpenAI, Anthropic, or open-source models).
 </li>
 <li>
 Solid understanding of prompt engineering techniques and LLM behavior.
 </li>
 <li>
 Experience with RAG systems and vector databases.
 </li>
 <li>
 Experience with data visualization tools (Tableau, Power BI, or similar).
 </li>
 <li>
 Basic knowledge of APIs, JSON/CSV formats, and Git version control.
 </li>
 <li>
 Comfortable working in cloud environments (AWS, Azure, or GCP).
 
 
 </li>
 </ul>
 
 Secondary Skills (Nice To Have)
 
 
 
 <ul>
 <li>
 Knowledge of vector embeddings and semantic search.
 </li>
 <li>
 Familiarity with LangChain, LlamaIndex, or similar frameworks.
 </li>
 <li>
 Experience working in Agile environments using Jira/Confluence.
 </li>
 <li>
 Background in software testing, QA, or SDLC processes.
 </li>
 <li>
 Experience in enterprise domains (financial services, insurance, retail).
 
 
 </li>
 </ul>
 
 Education
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, Data Science, Information Systems, or a related field.
 </li>
 </ul>
</div>

Prompt Engineer/Data Analyst

MOBIZ

<div>About Mobiz

Mobiz is an information technology firm, and we do three things exceptionally well: cloud and network automation, digital transformation, and data protection. Double-digit growth year-over-year has driven us to grow our team and ensure we stay ahead of the curve. 
What Can You Expect?

Every day at Mobiz we work with a deep sense of purpose. We continuously innovate. Our mission is to empower our clients to do more through transformation. You&rsquo;ll work in a collaborative environment alongside highly talented people that improve client operations and exceed expectations. We strive to simplify technology challenges, and no less. 


Who Are We Looking For?

We are looking for a skilled and motivated Data Engineer to join our growing data team. In this role, you will be responsible for designing, building, and operating scalable, secure, and high-performing data solutions that enable analytics, reporting, and data-driven decision-making across the organization. You will collaborate closely with cross-functional teams and leverage modern cloud technologies to transform raw data into trusted, accessible insights. 


Key Responsibilities
<ul>
<li>Design, build, test, deploy, and maintain robust data pipelines using Databricks, Azure Data Factory, and Microsoft Fabric, supporting both batch and streaming workloads.</li>
<li>Ingest, integrate, and harmonize data from multiple cloud and on-premises sources to deliver a unified, reliable, and trusted data view for analytics and reporting.</li>
<li>Use Python and SQL to clean, transform, validate, and model data to meet business, reporting, and analytical requirements.</li>
<li>Contribute to data architecture and platform design decisions, ensuring solutions are scalable, secure, cost-effective, and aligned with long-term business and technical strategy.</li>
<li>Build and maintain metadata-driven pipelines that gracefully adapt to schema changes, new data sources, and evolving ingestion patterns.</li>
<li>Proactively identify data quality issues, pipeline failures, and performance bottlenecks; perform root-cause analysis and implement durable, long-term solutions.</li>
<li>Continuously optimize data pipeline performance, reliability, and scalability to ensure fast, consistent, and dependable access to data.</li>
<li>Implement automated data quality checks, validation rules, and monitoring dashboards to ensure accuracy, consistency, and trust in delivered datasets.</li>
<li>Monitor, analyze, and manage data pipeline and compute costs across Azure, Databricks, and Microsoft Fabric, recommending and implementing cost-optimization strategies without compromising performance or availability.</li>
<li>Automate routine and repetitive data engineering tasks, applying best practices for CI/CD, deployment, testing, and operational support.</li>
<li>Design, implement, and maintain secure data access controls using role-based access, audits, and governance best practices to ensure appropriate data security and compliance.</li>
<li>Maintain clear, accurate, and up-to-date technical documentation, and provide ongoing operational support as data platforms and business needs evolve.</li>
<li>Stay current with emerging data engineering technologies, cloud services, and analytics best practices, and evaluate new tools through proofs of concept when appropriate.</li>
<li>Collaborate closely with product managers, software engineers, analysts, and operations teams to embed high-quality data solutions into core business processes.</li>
<li>Promote and enforce data engineering best practices including version control, modular and reusable pipeline design, documentation standards, and scalable architecture patterns.</li>
<li>Enable and support data democratization by providing well-modeled, secure, and self-service-ready datasets through Power BI, Microsoft Fabric, or custom analytics solutions.</li>
<li>Deliver measurable outcomes such as highly reliable pipelines with minimal manual intervention, on-time pipeline execution within service windows, rapid resolution of critical incidents, and consistently high data quality.</li>
<li>Ensure reusable and standardized pipeline components are leveraged across teams to accelerate delivery, improve consistency, and reduce operational overhead.</li>
<li>Provide stakeholders with reliable, well-modeled datasets that can be confidently explored without requiring ongoing engineering support.</li>
<li>Ensure all data solutions comply with organizational security, access, and governance policies while maintaining positive feedback from internal and external users.</li></ul> 


 Required Skills &amp; Qualifications 
<ul>
<li>3&ndash;5 years of hands-on experience in data engineering or related roles, with proven experience building, supporting, and operating production-grade data pipelines.</li>
<li>Strong hands-on experience with Databricks, including development, optimization, and operational support of Databricks-based data solutions.</li>
<li>Proven experience with Azure Data Factory (ADF) and Microsoft Fabric for data ingestion, orchestration, and transformation.</li>
<li>Advanced proficiency in SQL for querying, data modeling, performance tuning, and troubleshooting.</li>
<li>Strong programming skills in Python for data transformation, automation, scripting, and pipeline development.</li>
<li>Hands-on experience with Microsoft Azure cloud services related to data storage, compute, networking, and security.</li>
<li>Solid understanding of ETL/ELT patterns, data integration strategies, and real-time or near-real-time data processing concepts.</li>
<li>Experience designing metadata-driven and reusable pipeline components that scale across multiple teams and projects.</li>
<li>Strong understanding of data governance, data quality frameworks, monitoring practices, and automated validation techniques.</li>
<li>Experience supporting high-availability data platforms with SLAs, monitoring, alerting, and incident response processes.</li>
<li>Demonstrated ability to optimize cloud compute usage and manage costs efficiently across Azure, Databricks, and Microsoft Fabric.</li>
<li>Experience using version control systems such as Git and following modern software engineering best practices.</li>
<li>Ability to design secure, scalable, and cost-effective data architectures aligned with business needs.</li>
<li>Strong analytical, problem-solving, and troubleshooting skills with a proactive and ownership-driven mindset.</li>
<li>Excellent communication skills, with the ability to explain complex data concepts to both technical and non-technical stakeholders.</li>
<li>Ability to work independently as well as collaboratively in cross-functional team environments.</li>
<li>High attention to detail with a strong focus on data accuracy, reliability, and documentation quality.</li>
<li>Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field.</li>
<li>Relevant certifications are required or strongly preferred, including Databricks Certified Data Engineer, Microsoft Certified: Azure Data Engineer Associate, and Microsoft Certified: Fabric Data Engineer Associate.</li></ul> 


What We Offer
<ul>
<li>A team of bright, hard-working, and innovative people that will contribute to your growth.</li>
<li>Competitive Salary and comprehensive benefits plan.</li>
<li>A dynamic and collaborative work environment with opportunity to work with cutting-edge technology and innovative solutions.</li></ul> 


Other 
This is a full-time office based job in Islamabad, Pakistan. 
Closing

Mobiz embraces diversity and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we are. We are an equal opportunity employer.

We thank all applicants for their interest. We will contact you if you are selected to move forward in the recruiting process.</div>

Data Engineer

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Tajir | Software & Data Roles

Sr. Databricks Azure Data Engineer

AI Engineer

Quantitative Researcher

Quantitative Researcher

Prompt Engineer/Data Analyst

Data Engineer