As a Data Science AI Engineer, Professional 1 at Gainwell, you will support the development and implementation of data science, machine learning, and AI solutions that drive business insights and operational efficiency. You will collaborate with data teams, business stakeholders, and technology partners to analyze data, develop predictive models, and support AI-driven initiatives.
Your role in our mission
When joining Gainwell, you will:
Assist in designing, developing, and deploying data science, machine learning, and AI solutions to address business challenges.
Analyze structured and unstructured data to identify trends, patterns, and actionable insights.
Collaborate with cross-functional teams to gather requirements and support data-driven decision-making.
Develop and maintain data models, algorithms, dashboards, and reporting solutions that support business objectives.
Support continuous improvement efforts by evaluating emerging technologies, optimizing analytical processes, and ensuring data quality and integrity.
What we're looking for
2-4 years of experience in data science, machine learning, artificial intelligence, analytics, or a related field.
Experience using Python, SQL, R, or similar tools for data analysis, modeling, and solution development.
Knowledge of machine learning, predictive analytics, statistical modeling, and AI concepts.
Strong analytical, problem-solving, and critical-thinking skills with experience working with large datasets.
Strong communication and collaboration skills with the ability to present findings to technical and non-technical stakeholders.
What you should expect in this role
Remote, hybrid, or onsite work environment based on business and project needs.
... assumptions, feature engineering, code, validation, and performance rather than operating purely at a managerial level.- Education : Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Actuarial Science, Economics, or another highly quantitative discipline (preferred).- Domain Track Record ...
... assumptions, feature engineering, code, validation, and performance rather than operating purely at a managerial level.- Education : Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Actuarial Science, Economics, or another highly quantitative discipline (preferred).- Domain Track Record ...
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