AI/ML Engineer / Data Scientist

About Us:

Solytics Partners is a Global Analytics firm, recognized with multiple industry awards for innovation and excellence. Our team comprises experts with deep domain knowledge in risk, analytics, AI/ML, AML/FCC, and fraud. By converging this expertise with cutting-edge technologies like AI, Machine Learning, Generative AI, and Large Language Models (LLMs), we deliver powerful automated platforms and incisive point solutions.

Our offerings enable clients to streamline and future-proof their risk, AML, and analytics processes, comply seamlessly with global regulations, and safeguard financial systems. Whether it’s solving complex challenges or driving operational efficiency, Solytics Partners is committed to empowering organizations with transformative tools to stay ahead in an evolving regulatory landscape.

Job Summary:

We are looking for a highly motivated AI/ML Engineer / Data Scientist with hands-on experience in the end-to-end machine learning lifecycle, including exploratory data analysis (EDA), feature engineering, model development, training, and evaluation.

The ideal candidate should also have exposure to building intelligent, agentic AI workflows that automate various stages of the ML pipeline. This role will involve working closely with data scientists, engineers, and business stakeholders to develop scalable ML solutions and next-generation AI-driven automation frameworks.

Key Responsibilities:

* Perform exploratory data analysis (EDA) on structured and unstructured datasets to identify trends, anomalies, and business insights.

* Design and implement robust feature engineering pipelines for machine learning models.

* Develop, train, fine-tune, and optimize machine learning models for predictive and analytical use cases.

* Evaluate model performance using appropriate metrics and validation techniques, ensuring reliability and scalability.

* Build and maintain reproducible ML workflows and pipelines.

* Develop agentic AI workflows to automate tasks across the ML lifecycle, including data preparation, experimentation, model selection, evaluation, and reporting.

* Work with LLMs, AI agents, orchestration frameworks, and workflow automation tools to improve operational efficiency.

Key Requirements:

Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.

2–4 years of hands-on experience in machine learning and data science projects.

Strong experience in:

* Exploratory Data Analysis (EDA)

* Feature Engineering

* ML Model Training & Optimization

* ML Model Evaluation & Validation

Proficiency in Python (Django/ Flask/ FastAPI) and commonly used ML libraries/frameworks such as:

* Pandas

* NumPy

* Scikit-learn

* TensorFlow / PyTorch

Experience with SQL and working with large datasets.

Understanding of supervised and unsupervised learning techniques.

Experience in building or integrating agentic AI workflows and automation frameworks.