Senior Data Scientist

Devsinc, LLC; Lahore; On-site; PKR 1,800,000 - 3,600,000; Full time

Job summary

Devsinc, LLC in Lahore, Pakistan invites a Senior Data Scientist to join our data science team. You will develop and deploy ML models, explore AI-driven solutions, and work with stakeholders to translate data into actionable insights. Strong Python and ML framework experience is essential.

The role emphasizes building scalable pipelines, model evaluation, and collaboration with engineers and product teams. Generative AI familiarity is a plus.

Qualifications

• 3+ years of professional experience in data science and ML.
• Strong Python, Pandas, NumPy, Scikit-learn.
• Experience with ML frameworks: TensorFlow, PyTorch.
• Knowledge of Generative AI, LLMs, and prompt engineering.

Responsibilities

• Collect, clean, process, and analyze structured and unstructured data to identify patterns and opportunities.
• Develop, train, evaluate, and deploy ML models for real-world use cases.
• Build predictive, classification/recommendation, and forecasting systems.
• Use Python libraries for analysis, visualization, and modeling.

Skills

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Keras

SQL

Data visualization

REST APIs

Education

Bachelor’s in CS/DS/AI

Master’s in CS/DS/AI

Tools

LangChain

LlamaIndex

HuggingFace

MLflow

FastAPI

Docker

Git

AWS/Azure/GCP

Job description

We are looking for a skilled and results-driven Senior Data Scientist with 3+ years of professional experience in data science, machine learning, artificial intelligence, and predictive analytics. The ideal candidate should have strong expertise in Python, machine learning frameworks, statistical modeling, and AI-powered tools, with the ability to transform complex datasets into actionable business insights.

The candidate will be responsible for developing, training, evaluating, and deploying machine learning models, leveraging modern AI tools and frameworks to build scalable, data-driven solutions. Experience with Generative AI, Large Language Models (LLMs), and cloud-based AI services will be considered a strong advantage.

Key Responsibilities

• Collect, clean, process, and analyze structured and unstructured datasets to identify patterns, trends, and business opportunities.
• Develop, train, evaluate, and optimize machine learning and deep learning models for real-world applications.
• Build predictive models, classification and regression systems, recommendation engines, and forecasting solutions.
• Use Python libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn for data analysis, visualization, and model development.
• Work with machine learning and deep learning frameworks, including TensorFlow, PyTorch, and Keras.
• Leverage AI tools, Generative AI, LLMs, and prompt engineering techniques to develop intelligent applications and automate workflows.
• Apply statistical analysis, hypothesis testing, feature engineering, and model validation techniques to improve model performance.
• Develop data pipelines and integrate machine learning models into production applications through APIs and backend services.
• Collaborate with software engineers, data engineers, product managers, and business stakeholders to deliver AI-driven solutions.
• Monitor deployed models, evaluate performance, identify data drift, and implement improvements.
• Document technical processes, model architectures, experiments, and analytical findings.
• Stay updated with emerging AI technologies, machine learning methodologies, and industry best practices.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
• Strong proficiency in Python, Pandas, NumPy, and Scikit-learn.
• Hands‑on experience with Machine Learning, Deep Learning, TensorFlow, or PyTorch.
• Knowledge of Generative AI, LLMs, prompt engineering, RAG, and AI tools/frameworks such as LangChain, LlamaIndex, or Hugging Face.
• Strong understanding of statistics, data analysis, feature engineering, and model evaluation.
• Experience with SQL, data visualization tools, and REST APIs using FastAPI or Flask.
• Familiarity with AWS, Azure, or GCP, Docker, Git, and MLOps tools such as MLflow.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Generative AI, LLMs, RAG (Retrieval-Augmented Generation), embeddings, and vector databases.
• Familiarity with AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, OpenAI APIs, or equivalent technologies.
• Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Knowledge of MLOps practices, model monitoring, CI/CD pipelines, MLflow, or similar experiment-tracking tools.
• Experience processing large datasets and working with data engineering pipelines.
• Familiarity with NLP, computer vision, recommendation systems, or time-series forecasting