123 AI Researchers jobs in Pakistan

Qualifications: Bachelors or Masters degree in Computer Science, Statistics, or a related field.

Job Description: Data Science Position at Corvit Systems Multan.

About Company:
Corvit Systems is a leading provider of IT training in Multan. We offer courses from world-renowned vendors such as Cisco, Huawei, Juniper, Microsoft, VMware, Aruba, and Red Hat. Our training covers various domains including Routing, Switching, Security, Voice, Wireless, Data Center, Service Provider, Operating System, Virtualization, and Exchange Server/Email Server. We foster an encouraging and supportive environment that enhances the perception and technical intellect of individuals. Our goal is to unlock the inner potential of students and develop a competitive edge in the professional world.

1. Apply advanced statistical and machine learning techniques to analyze large datasets and extract valuable insights.
2. Develop predictive models and data-driven solutions to optimize business processes and drive decision-making.
3. Collaborate with cross-functional teams to identify and prioritize data science opportunities and challenges.
4. Clean, preprocess, and transform raw data to ensure accuracy and reliability.
5. Communicate complex findings and methodologies to both technical and non-technical stakeholders.
6. Stay up-to-date with the latest advancements in data science and relevant tools and technologies.
7. Use data visualization techniques to present results in a clear and meaningful way.

1. Strong analytical and problem-solving abilities with a keen eye for detail.
2. Proficiency in programming languages such as Python or R, and SQL.
3. Experience with statistical analysis, machine learning algorithms, and data visualization tools.
4. Solid understanding of data manipulation, data cleansing, and feature engineering techniques.
5. Excellent communication and presentation skills to convey complex information to diverse audiences.
6. Ability to work independently and collaboratively in a fast-paced, deadline-driven environment.
7. Strong business acumen and the ability to translate business requirements into data science solutions.

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.

Overview:
We’re looking for a hands-on Data Science & Engineering Lead to lead our data strategy and help scale a lean, high-impact team. This role blends leadership, architecture, and deep technical work - from building predictive models to designing the infrastructure that powers real-time decision-making. You’ll partner closely with cross-functional teams (Product, Business, Finance, Tech) and take full ownership of analytics delivery from raw data to actionable insight.

This is a builder’s role - ideal for someone who wants deep ownership, startup pace, and the chance to grow as we scale.

Responsibilities:

• Define and deliver our data strategy - from core infrastructure to insights delivery
• Build and mentor a team of 2–5 data scientists and engineers
• Design and deploy predictive models, recommendation systems, and performance analytics
• Architect, deploy, and maintain scalable data pipelines and analytics tooling
• Own and scale robust data pipelines and ensure data integrity across business verticals
• Collaborate closely with stakeholders across Product, Business Finance, and Tech teams to integrate data into daily operations and product decisions
• Act as the go-to person for data strategy, experimentation, and insights
  
  
  
  
  

• 5–6 years of relevant experience in data science, engineering or analytics,
• At least 1-2 years in a leading or mentoring small teams (leading 2-5 people) within an agile high tech environment
• Strong command of Python or R; strong SQL skills required
• Deep expertise in data analysis, predictive modeling, designing scalable pipelines, and maintaining analytics infrastructure
• Familiarity with modern BI tools (e.g., Looker, Metabase, Power BI, Tableau)
• Experience working cross functionally with business and product teams
• Startup mindset; strong bias for action, autonomy and ownership; able to apply agile principles and own delivery end to end
  
  
  
  

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Hospitality, Food and Beverage Services, and Retail

Referrals increase your chances of interviewing at Soum by 2x

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

Devsinc is on the lookout for Data Scientists with 6 months - 1.5 years of experience, with a particular focus on machine learning (ML). This role is ideal for individuals who have begun to develop their skills in ML methodologies and are eager to apply this knowledge to solve real-world challenges. The successful candidate will demonstrate a strong foundation in ML techniques, an analytical mindset for unraveling complex data puzzles, and a dedication to contributing to data-driven decisions and innovations.

Responsibilities:

1. Design, develop, and deploy machine learning models to address specific business challenges. This includes data preprocessing, feature engineering, model selection, training, and validation.
2. Perform exploratory data analysis to uncover hidden patterns, correlations, and insights within structured and unstructured data. Utilize these findings to refine ML models and approaches.
3. Engage with a multidisciplinary team of data scientists, engineers, and business stakeholders to refine data requirements and deliver ML-driven solutions.
4. Create clear visualizations to represent the outcomes of ML models and analyses. Prepare comprehensive reports and presentations that translate complex ML concepts and findings into actionable business insights.
5. Actively pursue learning opportunities in advanced machine learning techniques and algorithms. Incorporate cutting-edge research and tools into projects to enhance model performance and efficiency.
6. Assist in the development of prototypes for predictive models and other ML applications, testing their effectiveness in real-world scenarios.
7. Cross-Functional Application of Insights, Datasets, Code, and Models: Look for opportunities to use insights/datasets/code/models across other functions in the organization (for example in the HR and marketing departments).
8. Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
9. Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.

Minimum Requirements:

1. Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field with significant coursework or projects in machine learning.
2. A minimum of 6 months - 1.5 years of experience in machine learning or data science, with a portfolio demonstrating projects in ML model development, data analysis, and feature engineering. Solid proficiency in ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python. Experience with SQL and familiarity with data visualization libraries (e.g., Seaborn, ggplot2).
3. Exceptional skills in analyzing complex data sets to develop ML models that effectively address business needs.
4. Strong ability to communicate complex ML concepts and the results of analyses clearly to both technical and non-technical stakeholders.
5. Demonstrated ability to work effectively in a team, showing adaptability and openness to feedback.

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.