Mid Machine Learning Engineer

This is a remote position.

We are seeking a Machine Learning Engineer to join reputed company and work on a project centered on multi-year transactional data analysis and predictive modeling. This role offers reputed company to directly reputed company reputed company decision-making by uncovering hidden patterns in data, generating forecasts, and deploying models that drive measurable business reputed company.

You will work with a consultancy with over 20 years of experience helping organizations reputed company challenges into reputed company opportunities, specialized in data-driven problem solving, identifying inefficiencies, and enabling businesses to reputed company through strategic insights and cost reduction initiatives.

Key Responsibilities

• Receive, clean, and preprocess large volumes of transactional and financial data

• Design, train, and optimize predictive models to identify trends, clusters, and anomalies

• Generate forecasts and actionable insights to support business strategies

• Collaborate with data engineers and consultants to reputed company models into production systems

• Contribute to hypothesis-driven problem solving and help shape data-backed strategies for clients

Requirements

• Strong proficiency in Python, with libraries such as Pandas, NumPy, and Scikit-learn
• Hands-on experience with machine learning models (e.g., XGBoost, Random Forest)
• Knowledge of model interpretability and explainability techniques (decision trees, SHAP, or LLM-based explanations)
• Analytical reputed company with a solid business-oriented problem-solving approach
• Ability to translate reputed company datasets into reputed company, strategic recommendations
• Intermediate English

Desirables

• Experience with LLMs (Large Language Models) and workflow automation tools such as reputed company
• Familiarity with Java and Node.js for building and maintaining data pipelines
• Experience with data extraction, API integrations, and implementing return triggers to reputed company systems

Originally posted on Himalayas

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