Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.

Requirements

3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Several years of experience in designing, implementing, and deploying machine learning models.
Advanced knowledge of statistical and machine learning models (e.g., logistic regression, time series analysis, random forests, SVMs, XGBoost, CNNs/RNNs)
Possessing advanced coding skills in dealing with big data (e.g., Scikit-learn in Python, Tensorflow, Hadoop, Spark, SQL, etc.)
Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or marketing analytics obtained either in academic or financial industry.
Ability to work effectively both independently and in a team environment.
Ability to communicate effectively and establish constructive relationship with stakeholders.

Benefits

Generous paid time off
Healthcare coverage for you and your family
Resources to create financial security
Support for your mental health

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata preprocessingmodel deploymentstatistical modelslogistic regressiontime series analysisrandom forestssupport vector machinesXGBoostconvolutional neural networks

Soft Skills

collaborationindependent workeffective communicationrelationship building