Submitting more applications increases your chances of landing a job.
Here’s how busy the average job seeker was last month:
Opportunities viewed
Applications submitted
Keep exploring and applying to maximize your chances!
Looking for employers with a proven track record of hiring women?
Click here to explore opportunities now!You are invited to participate in a survey designed to help researchers understand how best to match workers to the types of jobs they are searching for
Would You Be Likely to Participate?
If selected, we will contact you via email with further instructions and details about your participation.
You will receive a $7 payout for answering the survey.
We’re hiring Data Scientists to join one of the world’s largest and most respected financial institutions! If you’re passionate about turning data into meaningful insights and building impactful AI solutions, we’d love to hear from you.
What you’ll be doing
In this role, you’ll design and develop scalable machine learning models and AI-driven solutions that tackle complex business challenges and support smarter decision-making.
Key Responsibilities
Work with large, complex datasets to solve real-world business problems.
Collect, clean, and preprocess data for analysis and model training.
Perform exploratory data analysis (EDA) to uncover insights and guide model development.
Build, train, and optimize machine learning models using modern algorithms and frameworks.
Develop end-to-end ML pipelines, from data ingestion to model deployment.
Automate model training, testing, and deployment using CI/CD and MLOps tools.
Collaborate with cross-functional teams to integrate models into production systems and deliver complete solutions.
What we’re looking for
5+ years of experience in data science, machine learning, or AI.
Strong knowledge of supervised and unsupervised learning, deep learning, and areas such as NLP, computer vision, or generative AI (including LLMs).
Proficiency in Python and/or R, with working knowledge of SQL.
Experience building data pipelines and working with big data tools (e.g. Spark, Airflow, Hadoop).
Understanding of model serving, APIs (FastAPI, Flask), and optimizing models for real-time or batch inference.
Familiarity with Docker, Kubernetes, CI/CD pipelines, and MLOps tools such as MLflow or Kubeflow.
Experience deploying models on cloud platforms like AWS, Google Cloud, or Azure (e.g. SageMaker, Vertex AI).
Bachelor’s degree in Computer Science, Engineering, or a related field.
If this sounds like the right next step for you, apply now!
You'll no longer be considered for this role and your application will be removed from the employer's inbox.