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Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader">Job Title: AI Data Scientist (Offshore)</h2>
Duration: 6 Months (Extendable) 
Experience: 6&ndash;8 Years 
Location: Offshore (Remote) 
Industry: Multi-Industry (with focus on Financial Sector) 
Employment Type: Contract (6 Months - Higher possiblity for extension)<h3 class="jobSectionHeader">
Job Summary</h3>
We are seeking a highly skilled AI Data Scientist with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the financial services domain. The ideal candidate will have strong proficiency in Python, SQL, and Google Cloud Platform (GCP) tools &mdash; leveraging platforms like BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker to deliver scalable and automated AI solutions.
This is an exciting 6-month contract role (with potential extension) focused on developing descriptive, predictive, and prescriptive models and deploying them in production using MLOps best practices.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3><ul><li>
Design and develop data science and machine learning models across descriptive, predictive, and prescriptive analytics.</li><li>
Work closely with business stakeholders&mdash;especially in the financial sector&mdash;to translate complex problems into AI-driven solutions.</li><li>
Develop and automate end-to-end ML pipelines on GCP using Vertex AI, Dataflow, Pub/Sub, and Dataproc.</li><li>
Implement MLOps frameworks for continuous integration, deployment, and monitoring of machine learning models.</li><li>
Analyze large datasets using BigQuery and other GCP-native tools for data transformation, feature engineering, and model training.</li><li>
Visualize insights and performance metrics using Looker and other BI tools.</li><li>
Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.</li><li>
Evaluate model performance and refine algorithms for improved accuracy and business impact.</li></ul><h3 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h3><ul><li>
5&ndash;8 years of professional experience in data science, AI/ML, and analytics roles.</li><li>
Proven expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL for data analysis and model development.</li><li>
Hands-on experience with GCP ecosystem, including:<ul><li>
BigQuery (data querying and transformation)</li><li>
Vertex AI (model training, tuning, deployment)</li><li>
Dataflow / Dataproc (data processing pipelines)</li><li>
Pub/Sub (event-driven data streaming)</li><li>
GCS (Google Cloud Storage) and Looker (visualization and reporting)</li></ul></li><li>
Strong knowledge of MLOps automation and continuous deployment best practices.</li><li>
Experience developing models in financial services (risk scoring, fraud detection, customer analytics, forecasting, etc.).</li><li>
Strong understanding of statistical modeling, feature engineering, and model performance evaluation.</li><li>
Excellent problem-solving and communication skills with ability to work in multi-industry environments.</li></ul><h3 class="jobSectionHeader"> 
Preferred Qualifications</h3><ul><li>
Experience in multi-cloud or hybrid environments.</li><li>
Knowledge of CI/CD pipelines for ML (GitHub Actions, Jenkins, or Cloud Build).</li><li>
Exposure to deep learning frameworks (TensorFlow, PyTorch).</li><li>
Experience in time-series forecasting, credit modeling, or financial risk analytics.</li></ul>
RE2l5yQYY6</div>

AI Data Scientist

Datamatics Technologies

<div>
 
 Job Title:
 
 AI Data Scientist (Offshore)
 
 
 
 Duration:
 
 6 Months (Extendable)
 
 
 Experience:
 
 &nbsp;6&ndash;8 Years
 
 
 Location:
 
 Offshore (Remote)
 
 
 Industry:
 
 Multi-Industry (with focus on Financial Sector)
 
 
 Employment Type:
 
 Contract (6 Months - Higher possiblity for extension)
 
 
 
 Job Summary
 
 
 We are seeking a highly skilled
 
 AI Data Scientist
 
 with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the
 
 financial services domain
 
 . The ideal candidate will have strong proficiency in
 
 Python, SQL
 
 , and
 
 Google Cloud Platform (GCP)
 
 tools &mdash; leveraging platforms like
 
 BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker
 
 to deliver scalable and automated AI solutions.
 
 
 This is an exciting
 
 6-month contract role (with potential extension)
 
 focused on developing
 
 descriptive, predictive, and prescriptive models
 
 and deploying them in production using
 
 MLOps best practices
 
 .
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 
 Design and develop
 
 data science and machine learning models
 
 across descriptive, predictive, and prescriptive analytics.
 
 </li>
 <li>
 
 Work closely with business stakeholders&mdash;especially in the
 
 financial sector
 
 &mdash;to translate complex problems into AI-driven solutions.
 
 </li>
 <li>
 
 Develop and automate
 
 end-to-end ML pipelines
 
 on
 
 GCP
 
 using Vertex AI, Dataflow, Pub/Sub, and Dataproc.
 
 </li>
 <li>
 
 Implement
 
 MLOps
 
 frameworks for continuous integration, deployment, and monitoring of machine learning models.
 
 </li>
 <li>
 
 Analyze large datasets using
 
 BigQuery
 
 and other GCP-native tools for data transformation, feature engineering, and model training.
 
 </li>
 <li>
 
 Visualize insights and performance metrics using
 
 Looker
 
 and other BI tools.
 
 </li>
 <li>
 
 Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.
 
 </li>
 <li>
 
 Evaluate model performance and refine algorithms for improved accuracy and business impact.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 <ul>
 <li>
 
 
 5&ndash;8 years
 
 of professional experience in
 
 data science, AI/ML
 
 , and analytics roles.
 
 </li>
 <li>
 
 Proven expertise in
 
 Python
 
 (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and
 
 SQL
 
 for data analysis and model development.
 
 </li>
 <li>
 
 Hands-on experience with
 
 GCP ecosystem
 
 , including:
 
 <ul>
 <li>
 
 
 BigQuery
 
 (data querying and transformation)
 
 </li>
 <li>
 
 
 Vertex AI
 
 (model training, tuning, deployment)
 
 </li>
 <li>
 
 
 Dataflow / Dataproc
 
 (data processing pipelines)
 
 </li>
 <li>
 
 
 Pub/Sub
 
 (event-driven data streaming)
 
 </li>
 <li>
 
 
 GCS (Google Cloud Storage)
 
 and
 
 Looker
 
 (visualization and reporting)
 
 </li>
 </ul>
 </li>
 <li>
 
 Strong knowledge of
 
 MLOps automation
 
 and continuous deployment best practices.
 
 </li>
 <li>
 
 Experience developing models in
 
 financial services
 
 (risk scoring, fraud detection, customer analytics, forecasting, etc.).
 
 </li>
 <li>
 
 Strong understanding of
 
 statistical modeling
 
 ,
 
 feature engineering
 
 , and
 
 model performance evaluation
 
 .
 
 </li>
 <li>
 
 Excellent problem-solving and communication skills with ability to work in multi-industry environments.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 
 Experience in
 
 multi-cloud
 
 or hybrid environments.
 
 </li>
 <li>
 
 Knowledge of
 
 CI/CD pipelines
 
 for ML (GitHub Actions, Jenkins, or Cloud Build).
 
 </li>
 <li>
 
 Exposure to
 
 deep learning frameworks
 
 (TensorFlow, PyTorch).
 
 </li>
 <li>
 
 Experience in
 
 time-series forecasting
 
 ,
 
 credit modeling
 
 , or
 
 financial risk analytics
 
 .
 
 </li>
 </ul>
</div>

ibex

<div>
 We are looking for a proactive and analytical
 
 Data Scientist
 
 to join our growing team. The ideal candidate will be deeply passionate about working with data, possess a strong foundation in statistical analysis and machine learning, and demonstrate the ability to derive actionable insights from complex datasets. This role requires experience in data wrangling, exploratory data analysis (EDA), and hands-on implementation of data science techniques, including Natural Language Processing (NLP).
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Collect, clean, and organize structured and unstructured data from diverse sources.
 </li>
 <li>
 Ensure data accuracy, consistency, and readiness for analysis.
 </li>
 <li>
 Perform thorough EDA to understand data distributions, relationships, and anomalies.
 </li>
 <li>
 Use visualization tools (e.g., Matplotlib, Seaborn, Pandas) to communicate findings.
 </li>
 <li>
 Work closely with business teams to identify trends and patterns that guide decisions.
 </li>
 <li>
 Handle missing data, outliers, and normalization techniques effectively.
 </li>
 <li>
 Transform raw data into features suitable for modeling and insights.
 </li>
 <li>
 Automate and optimize data preparation pipelines.
 </li>
 <li>
 Develop NLP pipelines for text classification, sentiment analysis, named entity recognition, and more.
 </li>
 <li>
 Work with tools such as NLTK, Hugging Face Transformers, and BERT-based models.
 </li>
 <li>
 Analyze and process unstructured text data for business use cases.
 </li>
 <li>
 Translate complex data problems into clear, actionable insights.
 </li>
 <li>
 Proactively identify opportunities for data-driven improvements across departments.
 </li>
 <li>
 Conduct root cause analysis and support hypothesis-driven investigations.
 </li>
 <li>
 Work closely with cross-functional teams including data engineers, analysts, and product stakeholders.
 </li>
 <li>
 Exhibit a high level of accountability, ownership, and willingness to support teammates.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, or a related field.
 </li>
 <li>
 2&ndash;3 years of experience in a data science role.
 </li>
 <li>
 Proficiency in Python (NumPy, Pandas, Scikit-learn), SQL and MongoDB
 </li>
 <li>
 Hands-on experience with NLP frameworks such as NLTK, or Hugging Face.
 </li>
 <li>
 Solid understanding of machine learning algorithms and data modeling techniques.
 </li>
 <li>
 Strong data visualization and storytelling skills.
 </li>
 <li>
 Excellent problem-solving and critical thinking abilities.
 </li>
 <li>
 Strong communication skills and a collaborative mindset.
 </li>
 </ul>
</div>

Data Scientist, Tech

Osol

<div>
 
 
 Company Overview
 
 
 
 Osol Tech Pvt. Ltd. is a fast-growing software development and professional services company, pioneering AI/ML-driven innovation across industries. We empower organizations in manufacturing, healthcare, retail, and e-commerce to make smarter, data-driven decisions through advanced analytics, predictive modeling, and AI solutions. Our culture fosters continuous learning, collaboration, and innovation at scale.
 
 
 
 
 
 
 Job Summary
 
 
 
 We are seeking a Senior Data Scientist to lead the design and implementation of advanced analytics and data science solutions. This role requires a strong foundation in statistics, machine learning, data engineering, and domain-driven problem solving.
 
 
 
 
 
 The ideal candidate will have experience building end-to-end data science solutions &mdash; from exploratory data analysis and feature engineering to production-ready models and business insights. You will collaborate closely with engineers, analysts, and business stakeholders to drive measurable outcomes.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, build, and evaluate predictive and prescriptive models (regression, classification, forecasting, clustering, recommendation systems).
 </li>
 <li>
 Apply advanced ML methods (gradient boosting, ensemble models, transformers for tabular/text, probabilistic models).
 </li>
 <li>
 Conduct A/B tests and causal inference to measure business impact.
 </li>
 <li>
 Perform exploratory data analysis (EDA) using statistical and visualization tools.
 </li>
 <li>
 Translate data findings into actionable insights with clear storytelling for non-technical audiences.
 </li>
 <li>
 Build dashboards and reports to support decision-making.
 </li>
 <li>
 Work with SQL, Spark, Dask, or BigQuery to process and transform large datasets.
 </li>
 <li>
 Collaborate with data engineers to ensure high-quality, reliable data pipelines.
 </li>
 <li>
 Apply feature engineering, data augmentation, and missing data handling strategies.
 </li>
 <li>
 Contribute to model deployment using MLflow, SageMaker, Vertex AI, or Azure ML.
 </li>
 <li>
 Support model monitoring and retraining strategies.
 </li>
 <li>
 Use Python (Pandas, NumPy, Scikit-learn, Statsmodels, PyTorch/TensorFlow), R, SQL, and Jupyter for analysis and modeling.
 </li>
 <li>
 Use visualization &amp; BI tools (Matplotlib, Seaborn, Plotly, Power BI, Tableau, Looker).
 </li>
 <li>
 Track experiments with MLflow, DVC, or Weights &amp; Biases.
 </li>
 <li>
 Partner with product managers and business teams to frame problems and define success metrics.
 </li>
 <li>
 Mentor junior data scientists and analysts.
 </li>
 <li>
 Champion data-driven decision-making across the organization.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications &amp; Skills
 
 
 <ul>
 <li>
 Strong programming skills in Python and SQL; familiarity with R or Julia is a plus.
 </li>
 <li>
 Solid foundation in statistics, probability, linear algebra, and hypothesis testing.
 </li>
 <li>
 Experience with machine learning techniques (supervised/unsupervised learning, ensembles, time series).
 </li>
 <li>
 Proficiency with data visualization and ability to communicate insights effectively.
 </li>
 <li>
 Hands-on experience with big data tools (Spark, Dask, BigQuery).
 </li>
 <li>
 Cloud experience with AWS, GCP, or Azure for data science workflows.
 </li>
 <li>
 Familiarity with version control (Git), experiment tracking, and reproducible workflows.
 </li>
 <li>
 Excellent communication, collaboration, and problem-solving skills.
 </li>
 <li>
 Proven ability to mentor junior engineers and lead initiatives.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Domain expertise in manufacturing, healthcare, retail, or e-commerce applications.
 </li>
 <li>
 Experience with NLP or computer vision applied to data-rich use cases.
 </li>
 <li>
 Hands-on experience with causal inference, Bayesian methods, or reinforcement learning for experimentation.
 </li>
 <li>
 Prior open-source contributions, publications, or patents.
 </li>
 <li>
 Experience with BI/analytics strategy and executive-level presentations.
 </li>
 </ul>
 
 
 
 
 
 Education &amp; Experience
 
 
 
 &bull; Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
 
 
 &bull; PhD or strong research experience is a plus, but not required.
 
 
 &bull; 5&ndash;7+ years of professional experience in data science or advanced analytics, with evidence of driving business impact.
 
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 High-impact data science projects that solve real-world problems.
 </li>
 <li>
 Continuous learning opportunities with cloud credits, courses, and conference sponsorships.
 </li>
 <li>
 Competitive salary, benefits, and performance-based incentives.
 </li>
 <li>
 Flexible hybrid/remote working environment.
 </li>
 <li>
 A culture of collaboration, innovation, and knowledge sharing.
 </li>
 </ul>
 
 
 
</div>

Senior Data Scientist

Game District

We are looking for a Data Analyst skilled in A/B testing to design experiments, analyze results, and optimize our products and marketing strategies. You will work closely with product and marketing teams to generate actionable insights and drive data-informed decisions. Strong SQL, statistical analysis, and data visualization skills are required, with experience in Python/R preferred.Key Responsibilities:<ul><li>Design, execute, and analyze A/B tests to evaluate product features, marketing campaigns, and user experience changes.</li><li>Collect, clean, and interpret data from multiple sources to generate actionable insights.</li><li>Develop dashboards, reports, and visualizations to communicate results effectively to stakeholders.</li><li>Collaborate with product, marketing, and engineering teams to define test hypotheses and metrics.</li><li>Conduct exploratory data analysis to identify trends, patterns, and opportunities for optimization.</li><li>Monitor ongoing experiments and ensure statistical rigor in test design and analysis.</li><li>Recommend data-driven improvements based on test results and analytics.</li></ul>Required Skills &amp; Qualifications:<ul><li>Bachelor&rsquo;s degree in Statistics, Mathematics, Economics, Computer Science, or a related field.</li><li>Proven experience in data analysis, preferably with A/B testing and experimentation.</li><li>Strong proficiency in SQL and experience with data visualization tools (e.g., Tableau, Power BI, Looker).</li><li>Knowledge of statistical methods, hypothesis testing, and experimental design.</li><li>Experience with analytics platforms like Google Analytics, Mixpanel, or similar tools.</li><li>Strong problem-solving skills and attention to detail.</li><li>Excellent communication skills to present findings to technical and non-technical audiences.</li><li>Experience with Python for data analysis.</li><li>Familiarity with product analytics and user behavior metrics.</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>What is your current salary? </li><li>What is your expected salary? </li><li>Please mention your total relevant experience. </li></ul>Work Location: In person

Data Analyst

Algo

<div>Job Title: Data Engineer 
Location: DHA Phase-8, Lahore 
 
Job Responsibilities: 
1. Design, build, and maintain efficient and scalable ETL/ELT data pipelines using tools like Azure Data Factory or Apache Airflow 
2. Develop, test, and deploy Python-based data processing solutions 
3. Work with Snowflake, Databricks and other data warehousing technologies to support data analytics and reporting needs 
4. Write complex and optimized SQL queries for data transformation and extraction 
5. Ensure data quality, accuracy, and compliance with internal and external standards 
6. Collaborate with data engineers, analysts, and stakeholders to define and implement data workflows 
7. Utilize version control (Git) and CI/CD pipelines for code deployment and process 
automation 
8. (Optional/Preferred) Support backend services using Django and task queues with 
Celery 

Qualifications Needed:
<ul>
<li>Python 
</li>
<li>SQL 
</li>
<li>Snowflake 
</li>
<li>Databricks 
</li>
<li>Azure (or AWS) 
</li>
<li>ETL/ELT 
</li>
<li>ADF / Apache Airflow 
</li>
<li>Data Warehousing 
</li>
<li>Git 
</li>
<li>CI/CD 
</li>
<li>Django (preferred) 
</li>
<li>Celery (preferred)</li></ul></div>

Data Engineer (4-5 Years)

Taraki

<div>
 
 About The Job
 
 
 
 <ul>
 <li>
 Build and maintain data pipelines using Python and Apache Spark.
 </li>
 <li>
 Orchestrate workflows using Airflow and Google Cloud Workflows (CloudFlow).
 </li>
 <li>
 Develop, deploy, and manage containerized data services using Docker and Cloud Run.
 </li>
 <li>
 Design, optimize, and monitor datasets and queries in BigQuery.
 </li>
 <li>
 Ingest, transform, and integrate external data through REST APIs.
 </li>
 <li>
 Manage data lifecycle and storage using Google Cloud Storage (GCS).
 </li>
 <li>
 Implement data quality, monitoring, and observability best practices.
 </li>
 <li>
 Collaborate with cross-functional engineering, product, and data science teams.
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 2&ndash;4+ years of experience as a Data Engineer or similar role.
 </li>
 <li>
 Strong proficiency in Python, SQL, and Spark/PySpark.
 </li>
 <li>
 Hands-on experience with Airflow and cloud-native orchestration (e.g., Cloud Workflows).
 </li>
 <li>
 Experience with Docker, containers, and deploying services in Cloud Run.
 </li>
 <li>
 Skilled with BigQuery, GCS, and general GCP data tooling.
 </li>
 <li>
 Experience working with REST APIs and building ingestion integrations.
 </li>
 <li>
 Solid understanding of data modeling, ETL/ELT pipelines, and distributed systems.
 
 
 
 </li>
 </ul>
 
 Bonus:
 
 Experience with healthcare data standards (FHIR, HL7) or regulated environments.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive salary and performance-based incentives
 </li>
 <li>
 Flexible work arrangements
 </li>
 <li>
 Paid time off and public holidays
 </li>
 <li>
 Professional development opportunities (training, workshops, certifications)
 </li>
 <li>
 Supportive, collaborative, and mission-driven work culture
 
 </li>
 </ul>
</div>

Data Engineer - Marham

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Data Engineer - Marham