38 Global Data jobs in Pakistan

FINCA Impact Finance (FIF) believes in the power of Inclusive Finance. FINCA Impact Finance is a global leader of responsible financial services. We are comprised of 17 full-service banks and microfinance institutions and a holding/shared service company and we serve more than 2.8 million customers with an array fintech and traditional products and services. We are a double bottom line company that delivers positive social impact and financial sustainability. We are 9,000 dedicated colleagues who are passionate that financial services can have a positive impact. Most of us living in the communities we serve, and all of us guided by our values of warmth, trust, and responsible banking. We welcome candidates with diverse backgrounds and considers people at all career stages. We seek individuals with whom we can build strong and lasting relationships - people who care about, and have respect for, customers. We look for colleagues who approach their work with joy, innovation, energy, and a sense of service beyond self. Thank you for applying. Role Purpose The Global Data Scientist is integral to the Global Data Management Office in supporting the Credit Risk function, use relevant data from a wide variety of sources to develop credit risk scoring models; provide practical, meaningful, and actionable insights to influence credit decisioning. The role is crucial in having the ability to assist risk and business in executing end-to-end data science projects using a proven structure and methodologic approach, allowing them to analyze trends, find patterns, predict the next best action, use artificial intelligence for process automation, make accurate predictions, and make better credit decisions that optimize FIF's value. Accountabilities Define data modelling requirements, gather, and validate information, apply judgment and statistical tests, and develop data structures to support the generation of business insights and strategy Drive development of in-house credit models, particularly developing scorecard models, enhance credit risk models (Behavioral and Application Credit Scoring Models) Utilize internal and external data sources and work on big data environment Work on data collection, data cleansing, methodology evaluation, model assessment, model refreshment, implementation testing and documentation Support implementation team(s) on model testing process including implementation specifications development, model testing development and execution to ensure model is appropriately implemented and produces output as designed Support throughout model lifecycle from model initiation to model retirement, including enhancements/recalibrations Execute monthly credit scoring models (internal) in accurate and timely manner for credit risk team Collect credit risk-related data and conduct analysis, segmentation, trending and forecasting. Actively examine alternative, internal, and external data sources to propose and/or review credit expansion and/or tightening measures, presenting and discussing alternatives, advantages, and disadvantages based on the data and industry expertise. Testing, validating, and overseeing the deployment of scorecards developed by external consultants for FIF Support ongoing BAU maintenance and upstream data changes into the enterprise data platforms. Support data projects through the provision of requirement specifications, UAT and Post implementation validation. Provide test interfaces for users to test the reports and dashboards before being put on the production environment and carry out technical user training as required to enable users to interpret BI solutions. Adhere to set Data Management standards and support the implementation of FIF's Data Strategy. Channel data issues to relevant support teams and proactively track them to their conclusion. Escalate any breach of SLAs or significant events to the Director Global Data Management Develop and maintain documentation/manuals on processes, procedures, models developed, reports generated, and statistical solutions devised. Conduct other ad hoc analysis as needed. Job Specification

Qualifications Bachelor’s Degree preferably in Statistics, Mathematics, Actuarial Science, Computer science or a related quantitative field and at least 4 years of hands-on experience in a busy commercial banking environment. A master’s degree is an added advantage. Experience A minimum of 4 years of proven data science & analytics performance. Experience with relational Databases such as Oracle, SQL queries, or OLAP cubes is preferred. Experience in the development of Credit Score Cards is a requirement. Experience with common Data Science toolkits, such as R, Python, Weka, NumPy, MatLab, etc. Excellence in at least R and/or Python is highly desirable. Experience in risk analytics (model development, strategy and framework, scorecard development, documentation, validation, governance, implementation, and automation etc.) Experience with Machine Learning modelling techniques Understanding credit bureaus and non-traditional data providers Proficiency in using query languages such as SQL, Hive, and Pig and Experience with NoSQL databases, such as MongoDB, Cassandra, and HBase. Knowledge and Skills Good Applied Statistics skills such as Distributions, Statistical Testing, and Regression Analysis with good Scripting and Programming skills. Knowledge of Agile Software Development process and performance metric tools. Excellent understanding of Machine learning techniques and Algorithms, such as k-NN, Naive Bayes, SVM and Decision Forests. Excellent understanding of data concepts and experience in data management capabilities including data definitions, data quality management and data integration. Good presentation skills, business and technical writing, and verbal communication skills to support decision-making and actions. Excellent problem-solving and critical thinking skills to recognize and comprehend complex data flow and designs. Self-motivated and able to dynamically determine priorities. Understanding of data governance issues, policies, regulatory requirements, and industry information affecting the business environment. Proven ability to collaborate with other team members across boundaries and contribute productively to the team’s work and output, demonstrating respect for different points of view. Able to use strong interpersonal and teamwork skills to cultivate effectively, productive user relationships and partnerships across the network. Highest personal and professional integrity and strong work ethic. Ability to articulate a vision of transformation efforts and a sense of mission. Results orientation, willingness to commit to a direction and drive operations to completion. Ability to break down complex problems and projects into manageable goals. Ability to get to the heart of the problem and make sound and timely decisions to resolve problems. Demonstrated ability to manage complexity and multiple initiatives coupled with the ability to synthesize and analyze diverse data and information, develop, and recommend strategies. Ability to think creatively with a strategic perspective, highly driven and self-motivated Analytical with good project management and team leadership skills. Strong commitment to the social mission of FINCA. Language Skills Fluency in English required Availability to travel up to 30% of the time

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The Big Data Engineer is responsible for designing, developing and managing big data platforms to process and analyze large datasets. You will work with cutting-edge technologies to ensure seamless data flow, scalability and high-performance systems. Your work will be crucial in providing actionable insights for decision-making across the business. Join us to shape the future of data-driven strategies.

Key Responsibilities

• Design Data Systems: Architect scalable data processing systems for business needs.
• Manage Data Pipelines: Build and maintain efficient data pipelines for real-time processing.
• Data Integration: Integrate disparate data sources for analysis and reporting.
• Ensure Data Quality: Implement methods for data cleaning and validation.
• Optimize Performance: Tune and optimize systems for speed and scalability.
• Collaborate with Teams: Work closely with data scientists and analysts to create solutions.
• Big Data Technologies: Work with Hadoop, Spark and similar big data tools.
• Security Compliance: Ensure data handling complies with privacy and security standards.

Qualifications

• 3+ years of experience in big data engineering or a similar role.
• Hands-on experience with big data platforms like Hadoop, Spark, or AWS.
• Previous work experience in developing and managing data pipelines.
• Strong programming skills in Python, Java, or Scala.
• Deep understanding of distributed computing systems and architectures.
• Ability to collaborate effectively across cross-functional teams.

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We are looking for enthusiastic and driven fresh graduates who have a strong interest and foundational understanding of Big Data concepts. As a Graduate Trainee – Big Data Analyst, you will be part of our dynamic Data & Analytics team, where you will be trained and mentored to work on real-world big data projects, tools, and technologies.

This is an excellent opportunity to start your career in the rapidly growing field of Big Data, working alongside experienced professionals in a fast-paced and innovative environment.

Key Responsibilities

• Assist in collecting, processing, and analyzing large volumes of structured and unstructured data.
• Support in building and maintaining data pipelines using big data technologies.
• Participate in data cleaning, transformation, and integration activities.
• Work with cross-functional teams to understand data requirements and provide data-driven insights.
• Learn and apply data processing in Data Lake & Apache Spark.
• Document processes and contribute to technical reports and dashboards.

Requirements

• Education: Bachelor’s degree in Computer Science or related fields (Graduated in 2025).
• Strong interest and foundational knowledge in Big Data, Data Science, or Data Engineering .
• Familiarity with programming languages such as Python, Java, or Scala .
• Exposure to SQL and basic understanding of databases (relational or NoSQL).
• Understanding of core big data concepts such as distributed computing, data lakes, and data warehousing is a plus.
• Willingness to learn and work with tools like Spark and Kafka etc.
• Excellent analytical thinking, problem-solving ability, and attention to detail.
• Strong communication and teamwork skills.

We have an amazing team of 700+ individuals working on highly innovative enterpriseprojects & products. Our customer base includes Fortune 100 retail and CPGcompanies, leadingstore chains, fast-growth fintech, and multipleSilicon Valley startups.

What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015,27001:2013 & 2000-1:2018 certified. We have a vibrant culture of learning via collaboration and making the 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:

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We are looking for enthusiastic and driven

fresh graduates

who have a strong interest and foundational understanding of

Big Data

concepts. As a Graduate Trainee – Big Data Analyst, you will be part of our dynamic Data & Analytics team, where you will be trained and mentored to work on real-world big data projects, tools, and technologies. This is an excellent opportunity to start your career in the rapidly growing field of Big Data, working alongside experienced professionals in a fast-paced and innovative environment. Key Responsibilities Assist in collecting, processing, and analyzing large volumes of structured and unstructured data. Support in building and maintaining data pipelines using big data technologies. Participate in data cleaning, transformation, and integration activities. Work with cross-functional teams to understand data requirements and provide data-driven insights. Learn and apply data processing in Data Lake & Apache Spark. Document processes and contribute to technical reports and dashboards. Requirements Education:

Bachelor’s degree in Computer Science or related fields (Graduated in 2025). Strong interest and foundational knowledge in

Big Data, Data Science, or Data Engineering . Familiarity with programming languages such as

Python, Java, or Scala . Exposure to SQL and basic understanding of databases (relational or NoSQL). Understanding of core big data concepts such as distributed computing, data lakes, and data warehousing is a plus. Willingness to learn and work with tools like Spark and Kafka etc. Excellent analytical thinking, problem-solving ability, and attention to detail. Strong communication and teamwork skills. We have an amazing team of 700+ individuals working on highly innovative enterpriseprojects & products. Our customer base includes Fortune 100 retail and CPGcompanies, leadingstore chains, fast-growth fintech, and multipleSilicon Valley startups. What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015,27001:2013 & 2000-1:2018 certified. We have a vibrant culture of learning via collaboration and making the 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:

Senior Data Science Engineer

Karachi

Remote

One-year contractual role

We are seeking a talented Data Scientist with strong expertise in SAS Viya and significant experience in
the banking and telecom sectors. In this role, you will leverage advanced analytics and machine learning
techniques to derive actionable insights from large datasets, optimizing business decisions and
strategies. Your knowledge of SAS Viya, along with your domain expertise, will be essential for
developing predictive models, improving customer experience, and enhancing operational efficiency.

Description

• Develop, implement, and fine-tune predictive and statistical models using SAS Viya to address
  business needs, with a focus on customer segmentation, churn prediction, fraud detection, and
  risk management in the banking and telecom sectors.
• Conduct deep data analysis and feature engineering to uncover patterns, trends, and insights
  that drive business strategies in banking and telecom operations.
• Integrate and process large datasets from various sources (e.g., transactional data, customer
  behavior data, financial data) and leverage SAS Viya’s cloud-native capabilities for scalable data
  processing and analysis.
  
• Apply machine learning algorithms and artificial intelligence techniques to develop models that
  enhance customer experience, optimize marketing campaigns, and improve operational
  efficiency.
• Present findings and insights through clear and actionable visualizations and reports using SAS
  Visual Analytics and other reporting tools, making complex data accessible to stakeholders.
• Continuously improve model performance by fine-tuning algorithms and optimizing data
  workflows to handle large volumes of data efficiently.

Requirements

• 5+ years of experience as a Data Scientist with a strong background in SAS Viya and experience
  working in banking and telecom sectors.
• Strong proficiency in SAS Viya (including SAS Visual Analytics, SAS Visual Data Mining and
  Machine Learning, and SAS Cloud Analytics).
• Experience with predictive modeling, statistical analysis, and machine learning algorithms in
  both sectors.
• Excellent communication skills, with the ability to translate technical findings into business
  insights for non-technical stakeholders.

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Senior Data Science Engineer

Karachi Remote One-year contractual role We are seeking a talented Data Scientist with strong expertise in SAS Viya and significant experience in the banking and telecom sectors. In this role, you will leverage advanced analytics and machine learning techniques to derive actionable insights from large datasets, optimizing business decisions and strategies. Your knowledge of SAS Viya, along with your domain expertise, will be essential for developing predictive models, improving customer experience, and enhancing operational efficiency. Description Develop, implement, and fine-tune predictive and statistical models using SAS Viya to address business needs, with a focus on customer segmentation, churn prediction, fraud detection, and risk management in the banking and telecom sectors. Conduct deep data analysis and feature engineering to uncover patterns, trends, and insights that drive business strategies in banking and telecom operations. Integrate and process large datasets from various sources (e.g., transactional data, customer behavior data, financial data) and leverage SAS Viya’s cloud-native capabilities for scalable data processing and analysis.

Apply machine learning algorithms and artificial intelligence techniques to develop models that enhance customer experience, optimize marketing campaigns, and improve operational efficiency. Present findings and insights through clear and actionable visualizations and reports using SAS Visual Analytics and other reporting tools, making complex data accessible to stakeholders. Continuously improve model performance by fine-tuning algorithms and optimizing data workflows to handle large volumes of data efficiently. Requirements 5+ years of experience as a Data Scientist with a strong background in SAS Viya and experience working in banking and telecom sectors. Strong proficiency in SAS Viya (including SAS Visual Analytics, SAS Visual Data Mining and Machine Learning, and SAS Cloud Analytics). Experience with predictive modeling, statistical analysis, and machine learning algorithms in both sectors. Excellent communication skills, with the ability to translate technical findings into business insights for non-technical stakeholders.

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Devsinc is seeking a talented Data Science Engineer who will play a pivotal role in designing, implementing, and optimizing data-driven solutions that enhance our machine learning capabilities. The ideal candidate has a strong background in data engineering combined with machine learning and is passionate about applying modern technologies to drive innovation. You will collaborate with data scientists, analysts, and software engineers to create robust data pipelines and deploy advanced models.

Key Responsibilities:

• Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources.
• Collaborate with data scientists to transform machine learning models into production-ready applications.
• Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process.
• Evaluate and integrate new data management and processing technologies to enhance analytics capabilities.
• Create and manage data repositories, following best practices for data governance and security.
• Develop documentation and provide training to team members on data systems and workflows.
• Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
• Stay updated on the latest industry trends and technologies in data engineering and machine learning.
• Lead the development and deployment of machine learning models that drive key business metrics and outcomes.
• Build and maintain scalable data pipelines and feature stores for training and inference use cases.
• Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery.
• Monitor and retrain models in production to ensure performance over time and handle data drift issues.
• Contribute to architectural decisions on data platforms and model-serving infrastructure.
• Mentor junior team members and help shape best practices in data science engineering.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline.
• 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions.
• Demonstrated experience translating business problems into data science projects with measurable outcomes.
• Prior experience working closely with business stakeholders to operationalize models and drive ROI.

Soft Skills:

• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills, both verbal and written, to convey technical concepts effectively.
• Ability to work collaboratively in a fast-paced team environment and manage multiple priorities.
• Motivated self-starter with a passion for learning and applying new technologies.

#J-18808-Ljbffr

Devsinc

is seeking a talented

Data Science Engineer

who will play a pivotal role in designing, implementing, and optimizing data-driven solutions that enhance our machine learning capabilities. The ideal candidate has a strong background in data engineering combined with machine learning and is passionate about applying modern technologies to drive innovation. You will collaborate with data scientists, analysts, and software engineers to create robust data pipelines and deploy advanced models. Key Responsibilities: Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources. Collaborate with data scientists to transform machine learning models into production-ready applications. Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process. Evaluate and integrate new data management and processing technologies to enhance analytics capabilities. Create and manage data repositories, following best practices for data governance and security. Develop documentation and provide training to team members on data systems and workflows. Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment. Stay updated on the latest industry trends and technologies in data engineering and machine learning. Lead the development and deployment of machine learning models that drive key business metrics and outcomes. Build and maintain scalable data pipelines and feature stores for training and inference use cases. Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery. Monitor and retrain models in production to ensure performance over time and handle data drift issues. Contribute to architectural decisions on data platforms and model-serving infrastructure. Mentor junior team members and help shape best practices in data science engineering. Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline. 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions. Demonstrated experience translating business problems into data science projects with measurable outcomes. Prior experience working closely with business stakeholders to operationalize models and drive ROI. Soft Skills: Strong analytical and problem-solving skills with attention to detail. Excellent communication skills, both verbal and written, to convey technical concepts effectively. Ability to work collaboratively in a fast-paced team environment and manage multiple priorities. Motivated self-starter with a passion for learning and applying new technologies.

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Join to apply for the Practice Lead (Data Science) role at Royal Cyber Inc.

3 weeks ago Be among the first 25 applicants

• 3-4 years of experience in a managerial role leading Data Science or Analytics teams
• Hands-on experience with programming languages (e.g., R, Python, Java), Spark, Snowflake, Databricks, AI, MLOPS
• Experience building, deploying, and scaling ML models for various problems
• Analyze and understand customer requirements through extensive data exploration
• Work directly with prospective customers’ technical resources to devise and recommend solutions based on understood requirements
• Work on POC and Pilot Projects to showcase the benefits of Advanced Analytics and Big Data Technologies
• Hands-on experience with Cloud platforms such as AWS, Azure, or GCP is preferred
• Present findings to IT and Business stakeholders
• Participate in brainstorming sessions to develop solutions/analytics
• Resource planning, staffing, and training
• Conduct webinars, seminars, attend conferences, produce content for blogs, white papers, and case studies for the company website and social media
• Minimum Master's Degree in Data Science, Computer Science, Business Administration, or Statistics; a Post Doctorate is a plus
• Deep learning experience is advantageous
• Business development and practice growth
• Project management skills
• Proven team management and client handling skills
• Strong statistical concepts
• Exposure to Artificial Intelligence and Deep Learning is a plus
• Ability and willingness to learn
• Strong analytical skills
• Flexibility with timings

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Consulting, Information Technology, and Sales

Industries

• IT Services and IT Consulting

Referrals can increase your chances of interviewing at Royal Cyber Inc. by 2x

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