Senior Staff Data Scientist (Growth)

Senior Staff Data Scientist to develop and implement machine learning models to drive business growth.

We are seeking a Senior Staff Data Scientist to join our dynamic team and take a leading role in developing cutting-edge machine learning systems that drive business growth.

As a key technical contributor, you will drive the development, deployment, and scalability of machine learning models in a production environment, ensuring they deliver value and performance at scale.

You will collaborate closely with data scientists, product teams and engineers to implement state-of-the-art solutions that power our consumer growth through continuous innovation.

What you’ll do

Design, develop, and implement cutting-edge statistical and machine learning models to effectively enhance consumer experiences and drive growth.
Take technical ownership of the end-to-end ML project life cycle, from data collection and preprocessing to model development, deployment, post-launch monitoring and maintenance, as well as sunsetting.
Leverage large-scale datasets to conduct exploratory data analysis and visualization, extracting actionable insights that guide strategic decision-making.
Collaborate with product managers, engineers, business and compliance stakeholders to understand requirements and translate them into technical solutions.
Build robust data pipelines and infrastructure to support model development, training, and deployment in a production environment.
Evaluate model performance, conduct A/B testing, and iterate on model improvements to enhance accuracy and effectiveness.
Stay current with industry trends, research advancements, and best practices in machine learning and fintech.

Key qualifications

Master’s or Ph.D. in Statistics, Mathematics, Computer Science, or a related quantitative field.
6+ years of experience in data science, specializing in statistical modeling and machine learning applied to real-world challenges.
Expertise in predictive modeling, optimization techniques, and causal inference to address complex business problems.
Strong proficiency in Python, R, or similar programming languages, with deep knowledge of statistical and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Hands-on experience with large datasets, cloud platforms (e.g., AWS, GCP), or distributed computing frameworks for data processing.
Proven track record of leveraging advanced statistical, machine learning, and data visualization techniques to drive measurable business outcomes.
Exceptional communication skills, with the ability to articulate complex technical models and insights to both technical and non-technical audiences.
Strong problem-solving abilities and a collaborative mindset, working effectively with cross-functional teams to develop and deploy impactful solutions.

The salary compensation range for this role will be commensurate with the candidate's experience and Flex's internal leveling guidelines and benchmarks.

For working locations in NY/NJ/CA, the base salary pay range will be $209,000-225,000
For all other states, the base salary pay range will be $188,000-203,000

What you’ll do

Design, develop, and implement cutting-edge statistical and machine learning models to effectively enhance consumer experiences and drive growth.

Take technical ownership of the end-to-end ML project life cycle, from data collection and preprocessing to model development, deployment, post-launch monitoring and maintenance, as well as sunsetting.

Leverage large-scale datasets to conduct exploratory data analysis and visualization, extracting actionable insights that guide strategic decision-making.

Collaborate with product managers, engineers, business and compliance stakeholders to understand requirements and translate them into technical solutions.

Build robust data pipelines and infrastructure to support model development, training, and deployment in a production environment.

Evaluate model performance, conduct A/B testing, and iterate on model improvements to enhance accuracy and effectiveness.

Stay current with industry trends, research advancements, and best practices in machine learning and fintech.

Key qualifications

Master’s or Ph.D. in Statistics, Mathematics, Computer Science, or a related quantitative field.

6+ years of experience in data science, specializing in statistical modeling and machine learning applied to real-world challenges.

Expertise in predictive modeling, optimization techniques, and causal inference to address complex business problems.

Strong proficiency in Python, R, or similar programming languages, with deep knowledge of statistical and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

Hands-on experience with large datasets, cloud platforms (e.g., AWS, GCP), or distributed computing frameworks for data processing.

Proven track record of leveraging advanced statistical, machine learning, and data visualization techniques to drive measurable business outcomes.

Exceptional communication skills, with the ability to articulate complex technical models and insights to both technical and non-technical audiences.

Strong problem-solving abilities and a collaborative mindset, working effectively with cross-functional teams to develop and deploy impactful solutions.

The salary compensation range for this role will be commensurate with the candidate's experience and Flex's internal leveling guidelines and benchmarks.

For working locations in NY/NJ/CA, the base salary pay range will be $209,000-225,000

For all other states, the base salary pay range will be $188,000-203,000