Senior Data Scientist (Beverly Hills)

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WHY JOIN ALO?

Mindful movement. It's at the core of why we do what we do at ALOit's our calling. Because mindful movement in the studio leads to better living. It changes who yogis are off the mat, making their lives and their communities better. That's the real meaning of studio-to-street : taking the consciousness from practice on the mat and putting it into practice in life.

WHY JOIN ALO?

Mindful movement. It's at the core of why we do what we do at ALOit's our calling. Because mindful movement in the studio leads to better living. It changes who yogis are off the mat, making their lives and their communities better. That's the real meaning of studio-to-street : taking the consciousness from practice on the mat and putting it into practice in life.

OVERVIEW

We are seeking an experienced Senior Data Scientist to join our team to lead the development of analytics and growth strategies across our entire business. The Senior Data Scientist will be responsible for managing and analyzing large data sets, developing statistical models and machine learning algorithms, and providing insights to drive business growth for our retail operations.

RESPONSIBILITIES

• Support the development of e-commerce and retail analytics and growth strategies, including market research, customer segmentation, and predictive modeling.
• Collaborate with cross-functional teams, including sales, marketing, product, and engineering to develop data-driven solutions that enhance customer experience and drive business growth.
• Develop statistical models and machine learning algorithms to analyze large data sets and identify opportunities to improve business performance.
• Build and maintain dashboards and reports that visualize data insights and performance metrics for executive leadership.
• Communicate complex data insights and models to non-technical stakeholders and translate findings into actionable recommendations.

QUALIFICATIONS

• Bachelor's or master's degree in a quantitative field, such as mathematics, statistics, or computer science
• PhD, or M.S. degree in a quantitative discipline such as CS, Statistics, ML, Physics, Economics, or Mathematics preferred
• 5+ years of experience in data science, including experience in DTC, e-commerce, or retail analytics
• Strong proficiency in statistical modeling and machine learning algorithms, such as regression analysis, clustering, and decision trees
• Experience with programming languages such as Python or R and SQL Jupyter, & ML libraries
• Strong communication and presentation skills, with the ability to translate complex data insights to non-technical stakeholders
• Strong leadership and / or management skills, with experience managing and mentoring a team of data scientists
• Proficiency in productionizing algorithms, from data ingest to model management, using AWS and / or Azure
• Self-starter : able to drive projects and take technical leadership of projects
• Experience in start-ups or other fast-paced environments preferred
• Experience and excitement partnering with Data Analytics and Data Engineering
• Currently based in the greater LA area or open to relocation and consent to working onsite full-time

The base salary range for this position is $160,000-$200,000 per year which represents the current range for the base salary for this exempt position. Please note that actual salaries will vary based on factors including but not limited to location, experience, and performance. As such, on occasion and when applicable, there is the possibility that the final, agreed-upon base salary may be outside of the upper end of the range. Please also note the range listed is just one component of the company's total rewards package for exempt employees. Other rewards may include performance bonuses, long term incentives, a PTO policy, and many other progressive benefits.

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Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Engineering and Information Technology

Industries

Retail Apparel and Fashion

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