PureSoftware - Senior Data Scientist - Generative AI

We are seeking a highly motivated Senior Data Scientist to develop data-driven solutions, build machine learning models, and generate actionable insights that drive business growth.

The ideal candidate will possess strong expertise in data science, statistical modeling, machine learning, and cloud-based data platforms, with the ability to translate complex business challenges into scalable analytical solutions.

Key Responsibilities

• Design, develop, and deploy machine learning and advanced analytics solutions to solve business problems and improve decision-making.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, anomalies, and actionable insights from large and complex datasets.
• Develop predictive, classification, clustering, forecasting, and recommendation models using statistical and machine learning techniques.
• Collaborate with business stakeholders, product teams, and engineering teams to understand requirements and deliver data-driven solutions.
• Design, build, and maintain scalable data pipelines and data processing workflows using AWS services and modern data engineering practices.
• Work with structured and unstructured data from multiple sources to support analytics and machine learning initiatives.
• Evaluate model performance, perform feature engineering, and optimize algorithms to improve accuracy and business impact.
• Deploy, monitor, and maintain machine learning models in production environments.
• Communicate analytical findings, recommendations, and business insights through reports, dashboards, and executive presentations.
• Ensure data quality, governance, and compliance standards are maintained throughout the analytics lifecycle.
• Stay current with emerging trends in Data Science, Artificial Intelligence, Machine Learning, and cloud technologies.

• 5-9 years of experience in Data Science, Machine Learning, Advanced Analytics, or related fields.
• Strong programming skills in Python and SQL; experience with R is an added advantage.
• Hands-on experience with machine learning libraries and frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar.
• Strong understanding of statistical analysis, predictive modeling, and data mining techniques.
• Experience working with large datasets and building scalable analytics solutions.
• Hands-on experience with AWS services such as S3, Lambda, Step Functions, and other cloud-native data services.
• Experience designing and maintaining data pipelines and ETL workflows.
• Strong knowledge of data visualization and reporting tools.
• Excellent analytical, problem-solving, and communication skills.
• Ability to effectively communicate technical concepts and insights to both technical and non-technical stakeholders.

• Experience with MLOps, model deployment, and monitoring frameworks.
• Exposure to Generative AI, LLMs, NLP, or Deep Learning use cases.
• Experience with Spark, Databricks, or distributed data processing platforms.
• Familiarity with Docker, Kubernetes, and CI/CD practices.
• Experience working in Agile development environments.

• A results-driven Data Scientist who combines strong analytical capabilities, machine learning expertise, and cloud-based data engineering experience to deliver scalable solutions and measurable business impact.