Releady
Data Scientist
Releady, San Francisco, California, United States, 94199
Overview
As a Senior Data Scientist, you will play a crucial role in driving analytical capabilities to the next level. Working closely with stakeholders across various departments, you will leverage your expertise in data analysis, machine learning, and statistical modeling to uncover insights, optimize processes, and contribute to strategic decision-making. You will lead projects from conception to implementation, mentoring junior data scientists and promoting a culture of excellence and continuous learning within the team.
Responsibilities
Lead complex data analysis projects to solve problems and uncover insights that inform company strategy and operations.Develop, deploy, and maintain machine learning models and algorithms to support various business initiatives.Champion the application of machine learning techniques in varied business contexts.Forge strong partnerships with business units to pinpoint areas ripe for innovation, crafting bespoke machine learning strategies from concept to realization.Guide technical direction by converting business objectives into data science solutions, collaborating with engineering teams to architect robust data pipelines.Undertake comprehensive reviews of contemporary statistical modeling techniques, underpinning the development of valid and innovative models.Facilitate the organization's evolution towards cloud computing and implement state-of-the-art practices in machine learning operations (MLOps).Proactively identify and mitigate potential obstacles in project workflows.Create detailed reports on project outcomes, while also providing mentorship and guidance to emerging talents in the team.Qualifications
Bachelor's or Master's degree in a quantitative field such as mathematics, statistics, or related field.5+ years of experience in data science or machine learning, demonstrating a capacity for translating complex business challenges into data-driven solutions.Robust experience with data manipulation and programming languages, including but not limited to SQL, Python, and R.Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).A solid foundation in a wide array of statistical methods and machine learning frameworks (e.g., TensorFlow, and PyTorch), with a keen eye for assessing model performance across various metrics.Commitment to best practices in MLOps, including documentation, testing, and version control, alongside proficiency in experimental design and hypothesis testing.Exceptional problem-solving abilities and quantitative aptitude.Excellent communication and interpersonal skills, with the ability to explain complex analytical concepts to non-technical stakeholders.Salary: $150k+
Location: Bay Area, California
Hybrid: Minimum of 3 days / week in officeWe are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.
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As a Senior Data Scientist, you will play a crucial role in driving analytical capabilities to the next level. Working closely with stakeholders across various departments, you will leverage your expertise in data analysis, machine learning, and statistical modeling to uncover insights, optimize processes, and contribute to strategic decision-making. You will lead projects from conception to implementation, mentoring junior data scientists and promoting a culture of excellence and continuous learning within the team.
Responsibilities
Lead complex data analysis projects to solve problems and uncover insights that inform company strategy and operations.Develop, deploy, and maintain machine learning models and algorithms to support various business initiatives.Champion the application of machine learning techniques in varied business contexts.Forge strong partnerships with business units to pinpoint areas ripe for innovation, crafting bespoke machine learning strategies from concept to realization.Guide technical direction by converting business objectives into data science solutions, collaborating with engineering teams to architect robust data pipelines.Undertake comprehensive reviews of contemporary statistical modeling techniques, underpinning the development of valid and innovative models.Facilitate the organization's evolution towards cloud computing and implement state-of-the-art practices in machine learning operations (MLOps).Proactively identify and mitigate potential obstacles in project workflows.Create detailed reports on project outcomes, while also providing mentorship and guidance to emerging talents in the team.Qualifications
Bachelor's or Master's degree in a quantitative field such as mathematics, statistics, or related field.5+ years of experience in data science or machine learning, demonstrating a capacity for translating complex business challenges into data-driven solutions.Robust experience with data manipulation and programming languages, including but not limited to SQL, Python, and R.Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).A solid foundation in a wide array of statistical methods and machine learning frameworks (e.g., TensorFlow, and PyTorch), with a keen eye for assessing model performance across various metrics.Commitment to best practices in MLOps, including documentation, testing, and version control, alongside proficiency in experimental design and hypothesis testing.Exceptional problem-solving abilities and quantitative aptitude.Excellent communication and interpersonal skills, with the ability to explain complex analytical concepts to non-technical stakeholders.Salary: $150k+
Location: Bay Area, California
Hybrid: Minimum of 3 days / week in officeWe are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.
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