Data Science Engineering Lead Manager
2 weeks ago
We're looking for a seasoned technical leader to join our Machine Learning and Optimization organization as an Engineering Lead Manager, Data Science. This critical role will oversee the research, development, and production of our ML and data science algorithms and usage of our data pipelines.
Our systems process over 350 billion auction events every day, and our transactions happen 24x7 in our global data centers. To achieve our mission, global efficiency and reliability are key, as every millisecond counts in our business.
Key Responsibilities:
- Technical Leadership: Chart a technical path for products, systems, and architectures, and lead from the front to guide others.
- People Leadership: Work with and lead a team of data scientists and machine learning engineers, demonstrating mentorship skills and setting a technical vision.
- Handler of Broad Scope: Thrive in environments with multiple projects and initiatives, self-managing time and resources to achieve the highest impact.
- Driver of Outcomes: Establish a vision or hypothesis, set a direction, and guide the team through execution, using data to inform pivots or validate assumptions.
- End-to-End Owner: Take pride in the products owned and delivered, taking full responsibility for their quality, health, and outcomes.
- Organizational Coordinator: Foster a collaborative approach to delivery, leveraging relationships to unblock dependencies and celebrate successes.
Requirements:
- Bachelor's degree or higher in Mathematics, Computer Science, Engineering, or equivalent.
- Demonstrated leadership and management of 3-10 person teams.
- Passion for cutting-edge technologies, leading teams, and nurturing talent development.
- Extensive experience in visualization and explanatory articulation of data science approaches, test and production results.
- Experience with ML and data science platforms and technologies.
- Experience with building and managing ML data pipeline to support data science and machine learning initiatives.
- Experience with data preparation and cleaning as well as data enrichment.
- Knowledge of big data stack including Kafka, Hadoop, Spark, Scala, and Airflow, as well as data warehouse technologies such as Vertica.
- Knowledge of BI tools like Looker and/or Redash will be very helpful.
- Experience with Docker and Kubernates is a plus.
Why Work at Index Exchange:
- Comprehensive health, dental, and vision plans at no cost to you.
- Time off and flexible work schedules.
- Retirement plan with a 5% company match.
- Stock options and equity packages.
- Generous parental leave.
- Monthly wellness stipend plus fitness discounts and quarterly wellness group activities.
- Community engagement opportunities and donation-matching program.
- Annual virtual company retreats and regular community-led team events.
- One day off per year to volunteer.
- A workplace that supports a diverse, equitable, and inclusive environment.
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