Unisys
Responsibilities
Collect, clean, and preprocess large datasets from multiple sources.
Apply statistical analysis and machine learning techniques to solve business problems.
Build predictive models and algorithms to optimize processes and improve outcomes.
Develop dashboards and visualizations to communicate insights effectively.
Collaborate with cross‑functional teams (Product, Engineering, Risk, Marketing) to identify opportunities for leveraging data.
Ensure data integrity, security, and compliance with organizational standards.
Stay current with emerging technologies and best practices in data science and AI.
Required Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
Strong proficiency in Python, R, SQL, and experience with data manipulation libraries (e.g., Pandas, NumPy).
Hands‑on experience with machine learning frameworks (e.g., scikit‑learn, TensorFlow, PyTorch).
Solid understanding of statistical modeling, hypothesis testing, and data visualization.
Experience with big data platforms (e.g., Spark, Hadoop) and cloud environments (AWS, Azure, GCP).
Excellent problem‑solving skills and ability to communicate complex concepts clearly.
Preferred Qualifications
Experience in risk modeling, financial services, or product analytics.
Knowledge of MLOps and deploying models in production.
Familiarity with data governance and compliance frameworks.
Soft Skills
Strong analytical thinking and attention to detail.
Ability to work independently and in a team environment.
Effective communication and stakeholder management skills.
Seniority Level Mid‑Senior level
Employment Type Contract
Job Function Information Technology
Industries IT Services and IT Consulting and Financial Services
#J-18808-Ljbffr
Collect, clean, and preprocess large datasets from multiple sources.
Apply statistical analysis and machine learning techniques to solve business problems.
Build predictive models and algorithms to optimize processes and improve outcomes.
Develop dashboards and visualizations to communicate insights effectively.
Collaborate with cross‑functional teams (Product, Engineering, Risk, Marketing) to identify opportunities for leveraging data.
Ensure data integrity, security, and compliance with organizational standards.
Stay current with emerging technologies and best practices in data science and AI.
Required Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
Strong proficiency in Python, R, SQL, and experience with data manipulation libraries (e.g., Pandas, NumPy).
Hands‑on experience with machine learning frameworks (e.g., scikit‑learn, TensorFlow, PyTorch).
Solid understanding of statistical modeling, hypothesis testing, and data visualization.
Experience with big data platforms (e.g., Spark, Hadoop) and cloud environments (AWS, Azure, GCP).
Excellent problem‑solving skills and ability to communicate complex concepts clearly.
Preferred Qualifications
Experience in risk modeling, financial services, or product analytics.
Knowledge of MLOps and deploying models in production.
Familiarity with data governance and compliance frameworks.
Soft Skills
Strong analytical thinking and attention to detail.
Ability to work independently and in a team environment.
Effective communication and stakeholder management skills.
Seniority Level Mid‑Senior level
Employment Type Contract
Job Function Information Technology
Industries IT Services and IT Consulting and Financial Services
#J-18808-Ljbffr