Your Team Responsibilities

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We are seeking a highly driven AI & Data Science Analyst with 3–4 years of hands-on industry experience to join our team. The ideal candidate has strong analytical and programming skills, is well-versed in modern AI/ML techniques, and can independently execute end-to-end data-driven solutions. You will work closely with cross-functional teams to design, develop, and deploy AI models, data workflows, and intelligent automation solutions that drive business impact

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Your Key Responsibilities

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Develop, train, evaluate, and optimize machine learning and deep learning models for various business use cases.

Build scalable data pipelines and workflows using Python and cloud services.

Perform exploratory data analysis (EDA), feature engineering, and model validation.

Collaborate with data engineers, product managers, and domain experts to understand business problems and identify AI-driven solutions.

Deploy and operationalize models using cloud platforms (AWS, Azure, or GCP).

Write clean, efficient, and well-documented Python code following best practices.

Create dashboards, reports, or visualizations to communicate insights effectively.

Stay up to date with emerging AI technologies, tools, and frameworks.

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Your skills and experience that will help you excel

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3–4 years of experience in AI, data science, or applied machine learning roles.

Strong proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.

Solid understanding of machine learning algorithms, statistical modeling, and data structures.

Experience with at least one cloud platform (AWS/Azure/GCP) for model deployment or data workflows.

Hands-on experience building and maintaining data pipelines.

Strong SQL knowledge and familiarity with relational or NoSQL databases.

Ability to translate complex technical concepts into clear business insights.

Excellent problem-solving, communication, and collaboration skills.

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Preferred Skills (Nice to Have)

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Experience with MLOps tools (Docker, Kubernetes, CI/CD, MLflow, SageMaker, Vertex AI, Databricks).

Familiarity with big data ecosystems (Spark, Hadoop).

Experience with LLMs, generative AI, prompt engineering, or model fine-tuning.

Knowledge of APIs, microservices, and cloud-native development.

Prior experience in financial analytics or risk/data domains (if applicable).

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