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junior / financial analyst

senior data scientist

i3Pathfinder Solutions (Pvt) Ltd

i3pathfinder soloutions (Pvt) Ltd is looking for Data Scientist for one of its client in karachi.1. Technical Skills<ul><li>Data mining or extracting usable data from valuable data sourcesCollaborate with Business and IT teams</li><li>Using machine learning tools to select features, create and optimize classifiers</li><li>Carrying out the preprocessing of structured and unstructured data</li><li>Enhancing data collection procedures to include all relevant information for developing analytic systems</li><li>Processing, cleansing, and validating the integrity of data to be used for analysis</li><li>Analyzing large amounts of information to find patterns and solutions</li><li>Developing prediction systems and machine learning algorithms</li><li>Presenting results in a clear manner</li><li>Propose solutions and strategies to tackle business challenges</li></ul><ul><li>Statistics &ndash; Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.</li><li>Machine Learning &ndash; good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.</li><li>Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.</li><li>Data Wrangling &ndash; proficiency in handling imperfections in data is an important aspect of a data scientist job description.</li></ul>Job Type: Contract Contract length: 12 monthsPay: Rs45,000.00 - Rs55,000.00 per monthWork Location: In person

Data Scientist

One Click Solution

OneClick is looking for a driven and analytical Applied Data Scientist with a strong focus on predictive modeling, forecasting, and applied machine learning. Location: Main Shahra-e-Faisal, Karachi Shift Timing: Morning (10:00 am &ndash; 6:00 pm), Monday to SaturdayKey Responsibilities:<ul><li>Analyze large, complex datasets using Python to uncover trends, patterns, and actionable insights.</li><li>Build, validate, and deploy predictive models and forecasting solutions to support data-driven decision-making.</li><li>Apply machine learning techniques (regression, classification, time-series forecasting, etc.) to solve business problems.</li><li>Automate data analysis workflows and modeling pipelines to improve efficiency and scalability.</li><li>Develop Power BI dashboards to communicate model-driven insights and forecasts to stakeholders.</li><li>Ensure data accuracy, integrity, and consistency across all analyses and reporting outputs.</li><li>Collaborate with cross-functional teams to translate business requirements into analytical solutions.</li></ul>Qualification and Requirements:<ul><li>Bachelor&rsquo;s degree in Data Science, Statistics, Computer Science, or a related field.</li><li>1&ndash;2 years of proven experience as a Data Scientist, Machine Learning Analyst, or similar role.</li><li>Strong proficiency in Python for data analysis, predictive modeling, and machine learning.</li><li>Hands-on experience with forecasting and predictive analytics techniques.</li><li>Experience using Power BI to visualize and present insights derived from analytical models.</li><li>Familiarity with automating data pipelines and analytical workflows is a plus.</li><li>Strong problem-solving skills with the ability to communicate complex insights clearly.</li></ul>Job Type: Full-timeWork Location: In person

Applied Data Scientist

Fiblix

Position Type: Full-Time, Remote Location: Remote (Worldwide) Reports to: Technical Director / CTOAbout the RoleWe are seeking a highly experienced AI/ML Engineer &amp; Data Scientist to work on a large-scale enterprise software platform. This is a senior-level position requiring deep expertise in artificial intelligence, machine learning, and data science with proven experience in building and deploying production-grade AI systems.You will be responsible for architecting intelligent features, building ML pipelines, integrating cutting-edge AI capabilities, and transforming complex data into actionable insights.Key ResponsibilitiesAI/ML Development<ul><li>Design and build end-to-end machine learning systems for production deployment</li><li>Develop deep learning models (CNNs, RNNs, Transformers, GANs)</li><li>Implement recommendation engines, predictive analytics, and intelligent automation</li><li>Optimize models for performance, scalability, and cost efficiency</li></ul>LLM &amp; NLP Integration<ul><li>Integrate and fine-tune Large Language Models (GPT-4, Claude, LLaMA, Mistral)</li><li>Build NLP pipelines for text classification, sentiment analysis, and entity recognition</li><li>Develop RAG systems, chatbots, and conversational AI features</li><li>Implement prompt engineering and chain-of-thought reasoning</li></ul>Data Science &amp; Analytics<ul><li>Conduct exploratory data analysis on large, complex datasets</li><li>Perform statistical analysis, hypothesis testing, and causal inference</li><li>Build automated data pipelines and feature engineering workflows</li><li>Create data visualizations and reporting dashboards</li></ul>MLOps &amp; Production Systems<ul><li>Design MLOps pipelines for continuous training and deployment</li><li>Implement model monitoring, drift detection, and automated retraining</li><li>Build scalable model serving infrastructure</li><li>Establish testing frameworks and deployment strategies</li></ul>AI Integrations<ul><li>Integrate third-party AI APIs (OpenAI, Anthropic, Google AI, Azure AI, AWS)</li><li>Design RESTful APIs for model serving</li><li>Implement vector databases and semantic search capabilities</li><li>Build microservices architecture for AI features</li></ul>Required QualificationsExperience<ul><li>Minimum 5-8 years in AI/ML and Data Science</li><li>Minimum 5 years deploying production ML systems at scale</li><li>Minimum 3 years with deep learning frameworks</li><li>Minimum 2 years with LLMs and modern NLP</li><li>Proven track record of delivering impactful AI projects</li></ul>Education<ul><li>Bachelor's in Computer Science, ML, AI, Data Science, Statistics, or related field</li></ul>Technical SkillsProgramming:<ul><li>Python (expert level), SQL, and one additional language (R, Scala, or Java)</li></ul>ML Frameworks:<ul><li>TensorFlow/Keras, PyTorch, Scikit-learn, XGBoost/LightGBM</li></ul>NLP &amp; LLMs:<ul><li>Hugging Face Transformers, LangChain, OpenAI/Anthropic APIs</li><li>Vector databases (Pinecone, Weaviate, Milvus, Chroma)</li></ul>MLOps:<ul><li>MLflow, Weights &amp; Biases, Docker, Kubernetes</li><li>Model serving (TensorFlow Serving, TorchServe, BentoML)</li></ul>Cloud Platforms (at least two):<ul><li>AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure ML</li></ul>Data Engineering:<ul><li>Apache Spark, data warehousing, stream processing</li></ul>Soft Skills<ul><li>Excellent English communication (written and verbal)</li><li>Self-motivated with ability to work independently</li><li>Strong problem-solving and analytical thinking</li><li>Experience working in remote, distributed teams</li></ul>Preferred Qualifications<ul><li>Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL)</li><li>Open-source contributions to ML frameworks</li><li>Experience with AI safety and alignment</li><li>Cloud ML certifications (AWS ML Specialty, GCP ML Engineer, Azure AI Engineer)</li><li>Domain expertise in enterprise software, fintech, healthcare, or e-commerce</li></ul>Job Type: Full-timePay: From Rs200,000.00 per month

Senior AI/ML Engineer & Data Scientist

Confiz

<div>We are seeking a Principal Data Engineer with 5+ years of hands-on experience and a strong background in real-time and batch data processing, containerization, and cloud-based data orchestration. This role is ideal for someone passionate about building robust, scalable, and efficient data pipelines, and who thrives in agile, collaborative environments.
Key Responsibilities
<ul><li>Design, build, and maintain real-time data pipelines using streaming frameworks such as Kafka, Apache Flink, and Spark Structured Streaming.</li>
<li>Develop batch processing workflows with Apache Spark (PySpark)</li>
<li>Orchestrate and schedule data workflows using orchestration frameworks such as Apache Airflow and Azure Data Factory</li>
<li>Containerize applications using Docker, manage deployments with Helm, and run them on Kubernetes</li>
<li>Implement modern storage solutions using open formats such as Parquet, Delta Lake, and Apache Iceberg</li>
<li>Build high-performance analytics engines using tools like Trino or Presto</li>
<li>Collaborate with DevOps to manage infrastructure with Terraform and integrate with CI/CD pipelines via Azure DevOps</li>
<li>Ensure data quality and consistency using tools like Great Expectations</li>
<li>Write modular, well-tested, and maintainable Python and SQL code</li>
<li>Develop an observability layer to monitor and optimize performance across data pipelines</li>
<li>Lead and mentor a team of data engineers</li>
<li>Participate in agile ceremonies and contribute to sprint planning and reviews</li>
</ul>
Required Skills &amp; Experience
<ul><li>Advanced Python programming with a strong focus on modular and testable code</li>
<li>Strong knowledge of SQL and experience working with large-scale datasets</li>
<li>Hands-on experience with at least one major cloud platform (Azure preferred)</li>
<li>Solid experience with real-time data processing (Kafka, Flink, or Spark Streaming)</li>
<li>Expertise in Apache Spark (PySpark) for batch processing</li>
<li>Experience implementing lakehouse architectures and working with columnar storage (e.g., ClickHouse)</li>
<li>Proficient in using Azure Data Factory or Apache Airflow for data orchestration</li>
<li>Experience in building APIs to expose large datasets</li>
<li>Solid experience with Docker, Kubernetes, and Helm</li>
<li>Familiarity with data lake open formats such as Parquet, Delta Lake, and Iceberg</li>
<li>Basic experience with Terraform for infrastructure provisioning</li>
<li>Practical experience with data quality frameworks (e.g., Great Expectations)</li>
<li>Comfortable working in agile development teams</li>
<li>Proven ability in debugging and performance tuning of streaming and batch data jobs</li>
<li>Experience with AI-driven tools (e.g., text-to-SQL) is a plus</li>
<li>Bachelor&rsquo;s degree in computer science or related discipline</li>
</ul>
We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM), ISO 14001:2015 (EMS), ISO 45001:2018 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/</div>

Principal Data Engineer (PySpark)

10Pearls

<div>Company Overview
10Pearls is an award-winning end-to-end digital innovation company that helps businesses imagine and build the future. We are proud to announce that 10Pearls was named the winner of the Best Tech Work Culture Timmy Award in Washington, D.C. by Tech in Motion, recognized on the Inc. 5000 Fastest-Growing Companies List, and was ranked the #1 Most Diverse Midsize Company in Greater Washington. We partner with businesses to help them transform, scale, and accelerate by adopting digital and exponential technologies. Our work has ranged from creating highly usable, secure digital experiences, mobile and software products, to helping businesses modernize through cloud adoption and development and the digitalization of their business processes. Our clientele is highly diverse, including Global 1000 enterprises, mid-market businesses, and even high-growth start-ups. But those are just facts. What makes us unique is that we have a true heart and soul. We have a strong focus on a double bottom line and actively support and engage with the communities where we live and work to make the world a better place. In a nutshell, we believe in doing well while doing good and know how to balance the two. 
 
Role 
 
We are seeking a skilled Data Engineer with strong expertise in Databricks and Snowflake to design, build, and optimize scalable data pipelines. You will work on high‑performance data processing workflows that support our platform, with a focus on real‑time analytics, large‑scale data transformations, and efficient data modeling. If you have experience with distributed data systems, cloud‑based data platforms, and modern data engineering best practices, we&rsquo;d love to hear from you. 
 
Responsibilities<ul><li>
Build and optimize data pipelines that ingest, validate, and transform core banking data (accounts, transactions, balances, parties, fees) from multiple source systems into our Databricks/Delta Lake lakehouse.</li><li>
Scale and evolve a multi‑tenant architecture, ensuring tenant isolation, efficient partitioning, and consistent schema evolution as we onboard new banks.</li><li>
Own CI/CD for the data platform, including GitHub Actions workflows, SQLMesh plan/apply lifecycle, and Databricks deployment automation.</li><li>
Develop and integrate ML models, including propensity scoring, churn prediction, segmentation, and customer scoring models that feed directly into analytics and decisioning layers.</li><li>
Ensure pipeline reliability through monitoring, alerting, and robust data validation across tenants and environments.</li><li>
Design and maintain 300+ SQL and Python data models across Bronze, Silver, and Gold layers using SQLMesh, with an emphasis on clean abstractions, reusability, and correctness.</li><li>
Own the metrics layer, defining and validating gold‑standard business metrics (revenue, attrition, household analytics, segmentation, balance projections) used by dashboards and APIs.</li><li>
Champion data quality by writing SQLMesh audits, unit tests, and enforcing schema contracts to ensure downstream consumers can trust the data.</li><li>
Collaborate with product and banking domain experts to translate business requirements into well‑modeled, documented, and performant data assets.</li><li>
Drive documentation and discoverability, ensuring data models are self‑describing and easily understood by analysts and product teams.</li></ul><h2 class="jobSectionHeader">
Requirement</h2><ul><li>
8+ years of software engineering experience, with deep expertise in data engineering and strong exposure to analytics engineering or data modeling.</li><li>
Production experience with SQLMesh or dbt, including building, testing, and deploying transformation projects (SQLMesh strongly preferred).</li><li>
Hands‑on experience with Databricks or Snowflake, operating pipelines and warehouses in production environments.</li><li>
Advanced SQL skills, including complex window functions, CTEs, incremental logic, and performance‑optimized aggregations.</li><li>
Proficiency in Python, especially for PySpark transformations, data validation, and pipeline automation.</li><li>
Strong understanding of dimensional modeling, medallion/layered architectures, and data quality best practices.</li><li>
Experience with CI/CD for data, including automated testing, version control, and deployment pipelines.</li></ul><h3 class="jobSectionHeader">
Nice‑to‑Have Qualifications</h3><ul><li>
Experience building or operationalizing ML models (propensity, churn, segmentation) within a data platform.</li><li>
Background in banking, financial services, or fintech data domains.</li><li>
Familiarity with Azure services (ADLS Gen2, Azure SQL, Databricks on Azure).</li><li>
Experience with multi‑tenant SaaS data architectures, including schema isolation and tenant‑aware partitioning.</li><li>
Exposure to data mesh concepts and domain‑oriented data ownership.</li><li>
Familiarity with Databricks Unity Catalog, Auto Loader, or Databricks Workflows.</li><li>
Experience with Linear, GitHub Actions, or similar project management and CI/CD tooling.</li></ul>
SxdPau6ofa</div>

Senior Software Consultant - Databricks / Snowflake - Afternoon

Rapid Labs

Senior Full Stack Machine Learning EngineerAbout Rapid LabsRapid Labs is a US based AI startup focused on building production ready, practical machine learning systems that solve real operational problems. We partner with businesses to design and deploy AI solutions that deliver measurable outcomes, not experiments or hype driven prototypes.Our culture values ownership, engineering excellence, and clear thinking. We work in fast moving, ambiguous environments where strong fundamentals and real world execution matter more than buzzwords.About the RoleWe are hiring a Senior Full Stack Machine Learning Engineer to own the design, development, and operation of production grade machine learning systems. This role is centered on applied and classical machine learning, not LLM only or prompt driven workflows.You will work close to the problem space, translating messy operational and business challenges into reliable ML systems that run in production. This is a hands on role for engineers who enjoy building, deploying, and improving real systems in the cloud and taking responsibility for outcomes.What You Will DoBuild and Own End to End ML Systems<ul><li>Own the full machine learning lifecycle from raw data to deployed, monitored, and continuously improving models</li><li>Design predictive, prescriptive, and optimization solutions for use cases such as manufacturing operations, predictive maintenance, quality analytics, and supply chain efficiency</li><li>Apply classical ML and statistical methods including time series forecasting, anomaly detection, regression, classification, clustering, probabilistic modeling, and optimization</li></ul>Engineer Strong Data and Feature Pipelines<ul><li>Build reliable ETL and ELT pipelines for batch and near real time ML workloads</li><li>Perform exploratory data analysis to understand data quality, distributions, bias, and signal</li><li>Design feature pipelines and feature stores that keep training and inference consistent</li><li>Integrate data from APIs, databases, and event streams with strong validation, schema control, and observability</li></ul>Ship and Operate Production ML<ul><li>Deploy models as scalable services using APIs, batch jobs, or streaming inference</li><li>Implement monitoring for model performance, drift, data quality, and system health</li><li>Work closely with platform and software teams to deliver secure, reliable, and cost efficient systems</li><li>Help define and enforce MLOps standards including CI CD, versioning, reproducibility, and rollback strategies</li></ul>Lead Technically and Collaborate Effectively<ul><li>Turn ambiguous business problems into clear ML problem statements, success metrics, and delivery plans</li><li>Make sound technical decisions on model selection, evaluation methods, and trade offs</li><li>Communicate results, risks, and limitations clearly to stakeholders using dashboards, visualizations, and documentation</li><li>Mentor junior engineers and raise the bar for ML engineering practices at Rapid Labs</li></ul>What We Are Looking ForMust Have<ul><li>Seven or more years of experience across machine learning engineering, data engineering, and production systems</li><li>At least five years of hands on experience delivering end to end machine learning solutions in production</li><li>Strong depth in classical machine learning and applied statistics beyond generative AI focused work</li><li>Solid understanding of evaluation techniques, validation strategies, bias variance trade offs, and failure modes</li><li>Advanced Python skills for production ML including clean code, testing, packaging, and performance tuning</li><li>Strong SQL skills and experience designing data models for analytics and ML</li><li>Three or more years of cloud experience with GCP preferred and AWS acceptable</li><li>Hands on experience with BigQuery, Cloud Storage, Dataflow or Apache Beam, Airflow or Cloud Composer, and containerized deployments using Docker and Kubernetes or managed equivalents</li><li>Experience operationalizing ML using tools such as MLflow, CI CD pipelines, workflow orchestration, and monitoring systems</li><li>Proven ability to monitor, debug, and improve models after deployment including drift detection and retraining</li><li>Strong problem solving skills with the ability to translate business needs into ML outcomes</li><li>Clear and confident communication skills with both technical and non-technical stakeholders</li><li>Experience working with cross functional teams including engineering, operations, and product</li></ul>Nice to Have<ul><li>Experience in manufacturing, industrial systems, or supply chain domains</li><li>Ownership of a technical roadmap or AI product lifecycle from planning to delivery</li><li>GCP or AI and ML related professional certifications</li><li>Background in consulting or client facing roles</li><li>Some exposure to GenAI or LLMs is welcome when combined with strong classical ML fundamentals, with LLMs used as supporting components rather than the core focus</li></ul>Salary &amp; Benefits<ul><li>Competitive salary and fringe benefits.</li><li>Paid Time off</li><li>Leaves encashment</li><li>EOBI</li><li>Professional Development</li><li>Career Advancement</li><li>Team Building Activities</li><li>Innovative Work Environment</li><li>Work-Life Balance</li><li>Company trips</li><li>Wellness Programs</li><li>Performance based promotion</li></ul>Location: Lahore Office, Islamabad Office, or Remote (Flexible)This role offers flexibility in how you work. Candidates may choose to join our Lahore office, work from our Islamabad office, or operate fully remote, depending on what works best for them.Office Hours: 05:00 PM to 02:00 AM (Monday to Friday) Job Type: Full-timeApplication Question(s):<ul><li>What is your current salary?</li><li>What is your expected salary?</li><li>What is the duration of your notice period in days?</li><li>Do you have 7+ years of experience as a Senior Full Stack Machine Learning Engineer?</li></ul>Experience:<ul><li>Senior Full Stack Machine Learning Engineer: 7 years (Preferred)</li></ul>Language:<ul><li>English fluently (Preferred)</li></ul>Work Location: In person

Senior Full Stack Machine Learning Engineer

Daraz

<div>
 
 Role Overview
 
 
 
 The Senior Key Account Manager will lead strategic engagement with key clients, drive revenue growth, and own portfolio performance for high-value FMCG and E-commerce partners. This role requires strong commercial acumen, analytical capabilities, and the ability to build lasting partnerships with stakeholders across retail and digital commerce ecosystems.
 
 
 Key Responsibilities
 
 
 Client &amp; Portfolio Management
 
 
 Build and strengthen long-term relationships with key customers and partners.
 
 
 Act as the primary point of contact for strategic accounts and ensure satisfaction, retention and growth.
 
 
 Develop and implement account plans with tailored solutions that enhance partner performance and business outcomes.
 
 
 Revenue &amp; Target Achievement
 
 
 Drive sales growth across assigned key accounts to meet and exceed revenue and profitability targets.
 
 
 Identify opportunities for upselling, cross-selling, and category expansion.
 
 
 Strategic Planning &amp; Execution
 
 
 Collaborate with internal teams (Marketing, Category, Supply, Analytics) to align commercial strategy with market demand.
 
 
 Monitor account performance and market trends; adjust plans to optimize growth.
 
 
 Negotiation &amp; Contract Management
 
 
 Lead negotiations for pricing, promotions, assortment, and commercial terms.
 
 
 Manage joint business planning (JBP) with strategic customers.
 
 
 Analysis &amp; Reporting
 
 
 Analyze sales data, customer insights and competitor activity to inform decision-making.
 
 
 Prepare weekly/monthly forecasts and pipeline reports for senior leadership.
 
 
 
 Qualifications
 
 
 
 
 Job Requirements
 
 
 
 Bachelor&rsquo;s degree in Business, Marketing, Sales, or related field.
 
 
 MBA or equivalent advanced business qualification preferred.
 
 
 5+ years of progressive experience in Key Account Management, FMCG, or E-commerce sectors.
 
 
 Demonstrated success owning and growing major client portfolios.
 
 
 
 Required Skills &amp; Competencies
 
 
 
 Commercial &amp; Analytical Acumen: Ability to analyze data and convert insights into clear, actionable growth plans.
 
 
 Stakeholder Management: Strong capability to build trusted relationships and influence senior decision-makers.
 
 
 Negotiation &amp; Strategic Thinking: Proven expertise in planning and leading complex commercial negotiations.
 
 
 Communication: Excellent verbal, written, and presentation skills.
 
 
 Leadership &amp; Collaboration: Effective cross-functional collaborator with experience mentoring junior team members.
 
 
 Tools &amp; Systems: Proficient in CRM, Excel, and business intelligence/analytics platforms.
</div>

Senior KAM, FMCG-Commercial

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