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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>

NorthBay Solutions

<div>
 
 
 
 
 
 
 Job Title
 
 
 
 
 
 
 
 
 
 
 
 
 : Data Scientist
 
 
 
 
 
 
 
 
 
 
 
 
 
 Location:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Lahore
 
 
 
 
 
 
 
 
 
 
 
 
 
 Job Type:
 
 
 
 
 
 
 
 
 
 
 
 
 Full-time, (Hybrid)
 
 
 
 
 
 
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 
 
 
 
 
 
 
 
 NorthBay is seeking a skilled Data Scientist with 4+ years of professional experience to join our team. The ideal candidate will have hands-on experience in data processing, visualization, and structuring, along with practical exposure to Large Language Models (LLMs) and agentic AI systems. You will work on designing intelligent data workflows, integrating AI models, and developing predictive analytics to support business decision-making. Strong analytical, problem-solving, and communication skills are essential, as the role involves close collaboration with cross-functional stakeholders.
 
 
 
 
 
 
 
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Design, implement, and optimize LLM-powered features and agentic AI workflows.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Develop and maintain data pipelines for extracting, structuring, and processing large datasets.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Integrate LLMs (e.g., GPT, Claude, Gemini, Llama) into data workflows to enhance automation and insight generation.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Collaborate with technical and business teams to identify opportunities for LLM and agentic AI adoption in operational processes.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Build Python-based tools and scripts for data manipulation, visualization, and decision automation.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Utilize relational databases (SQL Server, MySQL, etc.) for data extraction and analysis.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Research and evaluate modern open-source and proprietary AI/ML models to support project requirements.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Implement monitoring and automated data validation processes to ensure quality and scalability.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Contribute to GenAI initiatives and experimentation with emerging AI frameworks.
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Requirements:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 4+ years of professional experience in data science, data engineering, or AI-focused roles.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 2+ years of hands-on experience working with LLMs (GPT, Claude, Gemini, Llama, etc.) and agentic AI systems.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 1+ year of experience working with relational databases (SQL Server, MySQL, PostgreSQL, etc.).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Strong proficiency in Python for data manipulation, automation, API integration, and prompt engineering.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Experience with data structuring, cleaning, processing, and visualization tools.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Experience building and deploying data-driven or AI-assisted solutions.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Good-to-have: Exposure to .NET for application integration or workflow development.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Strong communication skills with the ability to translate technical findings into actionable business insights.
 
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 If you meet the above qualifications and are excited to work on innovative AI-driven data solutions, we encourage you to apply and join our team!
 
 
 
 
 
 
</div>

Data Scientist

NorthBay - Pakistan

<div>
 Job Title: Data Scientist
 
 
 Location: Lahore
 
 
 Job Type: Full-time, (Hybrid)
 
 
 
 Job Description
 
 
 
 NorthBay is seeking a skilled Data Scientist with 4+ years of professional experience to join our team. The ideal candidate will have hands-on experience in data processing, visualization, and structuring, along with practical exposure to Large Language Models (LLMs) and agentic AI systems. You will work on designing intelligent data workflows, integrating AI models, and developing predictive analytics to support business decision-making. Strong analytical, problem-solving, and communication skills are essential, as the role involves close collaboration with cross-functional stakeholders.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and optimize LLM-powered features and agentic AI workflows.
 </li>
 <li>
 Develop and maintain data pipelines for extracting, structuring, and processing large datasets.
 </li>
 <li>
 Integrate LLMs (e.g., GPT, Claude, Gemini, Llama) into data workflows to enhance automation and insight generation.
 </li>
 <li>
 Collaborate with technical and business teams to identify opportunities for LLM and agentic AI adoption in operational processes.
 </li>
 <li>
 Build Python-based tools and scripts for data manipulation, visualization, and decision automation.
 </li>
 <li>
 Utilize relational databases (SQL Server, MySQL, etc.) for data extraction and analysis.
 </li>
 <li>
 Research and evaluate modern open-source and proprietary AI/ML models to support project requirements.
 </li>
 <li>
 Implement monitoring and automated data validation processes to ensure quality and scalability.
 </li>
 <li>
 Contribute to GenAI initiatives and experimentation with emerging AI frameworks.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 4+ years of professional experience in data science, data engineering, or AI-focused roles.
 </li>
 <li>
 2+ years of hands-on experience working with LLMs (GPT, Claude, Gemini, Llama, etc.) and agentic AI systems.
 </li>
 <li>
 1+ year of experience working with relational databases (SQL Server, MySQL, PostgreSQL, etc.).
 </li>
 <li>
 Strong proficiency in Python for data manipulation, automation, API integration, and prompt engineering.
 </li>
 <li>
 Experience with data structuring, cleaning, processing, and visualization tools.
 </li>
 <li>
 Experience building and deploying data-driven or AI-assisted solutions.
 </li>
 <li>
 Good-to-have: Exposure to .NET for application integration or workflow development.
 </li>
 <li>
 Strong communication skills with the ability to translate technical findings into actionable business insights.
 
 
 </li>
 </ul>
 If you meet the above qualifications and are excited to work on innovative AI-driven data solutions, we encourage you to apply and join our team!
</div>

<div><h3 class="jobSectionHeader">Job Title: Data Scientist</h3>
Location: Lahore<h4 class="jobSectionHeader">
Job Type: Full-time, (Hybrid)</h4><h3 class="jobSectionHeader">
Job Description:</h3>
NorthBay is seeking a skilled Data Scientist with 4+ years of professional experience to join our team. The ideal candidate will have hands-on experience in data processing, visualization, and structuring, along with practical exposure to Large Language Models (LLMs) and agentic AI systems. You will work on designing intelligent data workflows, integrating AI models, and developing predictive analytics to support business decision-making. Strong analytical, problem-solving, and communication skills are essential, as the role involves close collaboration with cross-functional stakeholders.<h2 class="jobSectionHeader">
Key Responsibilities:</h2><ul><li>
Design, implement, and optimize LLM-powered features and agentic AI workflows.</li><li>
Develop and maintain data pipelines for extracting, structuring, and processing large datasets.</li><li>
Integrate LLMs (e.g., GPT, Claude, Gemini, Llama) into data workflows to enhance automation and insight generation.</li><li>
Collaborate with technical and business teams to identify opportunities for LLM and agentic AI adoption in operational processes.</li><li>
Build Python-based tools and scripts for data manipulation, visualization, and decision automation.</li><li>
Utilize relational databases (SQL Server, MySQL, etc.) for data extraction and analysis.</li><li>
Research and evaluate modern open-source and proprietary AI/ML models to support project requirements.</li><li>
Implement monitoring and automated data validation processes to ensure quality and scalability.</li><li>
Contribute to GenAI initiatives and experimentation with emerging AI frameworks.</li></ul><h2 class="jobSectionHeader">
Requirements:</h2><ul><li>
4+ years of professional experience in data science, data engineering, or AI-focused roles.</li><li>
2+ years of hands-on experience working with LLMs (GPT, Claude, Gemini, Llama, etc.) and agentic AI systems.</li><li>
1+ year of experience working with relational databases (SQL Server, MySQL, PostgreSQL, etc.).</li><li>
Strong proficiency in Python for data manipulation, automation, API integration, and prompt engineering.</li><li>
Experience with data structuring, cleaning, processing, and visualization tools.</li><li>
Experience building and deploying data-driven or AI-assisted solutions.</li><li>
Good-to-have: Exposure to .NET for application integration or workflow development.</li><li>
Strong communication skills with the ability to translate technical findings into actionable business insights.</li></ul> 
If you meet the above qualifications and are excited to work on innovative AI-driven data solutions, we encourage you to apply and join our team!
2Kn8jJxVIr</div>

Taraki

<div>
 Taraki is hiring for one of its clients.
 
 
 Location: Remote
 
 
 Experience Level: 5 to 8 years in Applied Machine Learning, Statistical Modeling, and Data Science for large-scale systems Department: Data &amp; AI Engineering
 
 
 Compensation: PKR 600,000 to 850,000 (based on experience)
 
 
 Role Summary:
 
 
 The Data Scientist will develop ML models to predict customer behavior, price sensitivity, and offer conversion probability. They will build and maintain elasticity models, segmentation models, and reinforcement learning frameworks to enable personalized pricing and offer recommendations.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Build and deploy models for:
 </li>
 <ul>
 <li>
 Price Elasticity / Conversion Prediction
 </li>
 <li>
 Churn Propensity / Retention Uplift
 </li>
 <li>
 Segment Discovery &amp; Similarity (Clustering, KNN)
 </li>
 <li>
 Offer Recommendation / Ranking (Scoring Models)
 
 </li>
 </ul>
 <li>
 Design A/B testing and uplift modeling to evaluate campaign performance.
 </li>
 <li>
 Develop simulation engines for pricing what-if analysis and scenario testing.
 </li>
 <li>
 Create automated pipelines for model training, scoring, and retraining.
 </li>
 <li>
 Work closely with Data Engineers to ensure feature store alignment.
 </li>
 <li>
 Collaborate with the Business Decisioning team to translate insights into rules and thresholds.
 </li>
 <li>
 Implement feedback loops using real-time events (purchase, rejection, expiry) to improve models.
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 <ul>
 <li>
 Strong foundation in Machine Learning, Statistics, and Econometrics.
 </li>
 <li>
 Proficient in Python (pandas, scikit-learn, numpy, statsmodels, xgboost, lightGBM).
 </li>
 <li>
 Experience with model lifecycle management (MLOps).
 </li>
 <li>
 Solid understanding of telecom KPIs: ARPU, recharge frequency, wallet size, churn rate, etc.
 </li>
 <li>
 Ability to design feature engineering pipelines and perform A/B testing.
 </li>
 <li>
 Expertise in data visualization and storytelling for non-technical stakeholders.
 
 
 
 </li>
 </ul>
 Tools &amp; Technologies
 
 
 Data Science: Python, R, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch
 
 
 MLOps: MLflow, SageMaker, Databricks ML, Azure ML Studio
 
 
 Data: Databricks, Snowflake, S3, Delta Lake
 
 
 Visualization: PowerBI, Tableau, Streamlit, Dash
 
 
 Experimentation: Evidently AI, CausalML, upliftML
 
 
 Versioning: Git, DVC, MLflow Tracking
 
 
 
 Preferred (Nice-to-Have)
 
 
 
 <ul>
 <li>
 Experience with Telecom Offer &amp; Recharge Modeling or Dynamic Pricing Systems.
 </li>
 <li>
 Knowledge of Pricefx PriceAI, Adobe Target Recommendations, or Reinforcement Learning frameworks.
 </li>
 <li>
 Understanding of Elasticity Curves, Customer Lifetime Value (CLV), and Offer Fatigue Modeling.
 </li>
 <li>
 Experience integrating ML outputs into business decision engines or rule systems.
 </li>
 </ul>
</div>

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

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