Engineering Manager, Data Science and Intelligence

Key Skills

A/B Testing, Algorithms, Analytical and Problem solving, Large Language Models - LLMs, Machine learning techniques, PyTorch, Scikit-learn, TensorFlow

Job Description

Engineering Manager, Data Science and Intelligence

Brightflow AI is making cash management and forecasting accessible to the everyday business owner. Founded in Fall 2019, with the goal of democratizing finance, our rapidly growing and well-funded startup is in need of exceptional engineers to join us as we climb to the next level.

About the Role

As an engineering manager for Data Science and Intelligence group, you will partner across the Product Engineering org and represent the team as the data science and intelligence thought leader and set directions for the team to deliver innovative machine learning solutions using our huge reservoir of 1st party and 3rd party data. You will work with data analysts, ML engineers, data engineers, product managers and fellow engineering managers to turn machine learning models into business insights for our customers.

• Lead, influence and contribute across Data Science and Intelligence team to drive business value for Brightflow and our customers
• Collaborate closely with product and engineering stakeholders to drive strategic direction for Brightflow’s AI-enabled product and toolkits
• Work closely with Platform team to help shape and execute the brightflow's AI architecture
• Drive clarity for the team - break down larger ML initiatives into smaller problems that enables engineers to deliver incremental business value and lead the team to execute on them
• Work with financial advisers, product managers to deliver the bespoke data analytics solutions to VIP customers
• Incorporate up-to-date DS approach as best practices for the team
• Coach and mentor team members to be successful in their career growth
• Work and lead effectively in a dynamic, changing environment while focusing on key goals and objectives

Why you’ll love working here

First, working on interesting problems in a place for growth: Given the volatility of the market, our tool is addressing the pain point of small business owners. We are positioned to grow. The team is currently small and expanding, you can be influential.

Secondly, be with a great culture and great people: trust and psychological safety are high - you can expect to be challenged and given a place to do great work. Our culture fosters transparent, appreciative feedback, respect, and empathy.

The team is experienced and knowledgeable, strong finance experience (including Capital One, VC firms) and engineering backgrounds at multiple early-stage startups, and previous experience as founder and CEO of a YC startup.

What We’re Looking For

• 7+ years of working experience in Data Science, ML with 2+ years in managing roles
• Strong knowledge of underlying mathematical foundations of statistics and machine learning
• Demonstrated excellence in a relevant AI/ML discipline (NLP, etc.), including experience with ML model building with libraries such as Scikit, Tensorflow and PyTorch, significant experience in applying LLM. Have knowledge of fundamentals of machine learning, such as algorithm families (regression, classification, unsupervised), AB testing, hypothesis testing, and optimization
• Good balance between engineering mindsets and science methodology to enable creative problem solving
• Experience in managing both bespoke data solutions and data products and know how to convert the learning in bespoke solution to product
• Result oriented and has strong bias for action, experienced in collaborating with cross-functional teams and product stakeholders
• Strong communication skills, demonstrated through documentation and presentations. Able to present findings to senior management to inform business decisions
• Experience in mentoring and growing a data science and intelligence team

Beneficial but not required:

• Advanced degree in Data Science, Statistics, Applied Math, Computer Science, Engineering or other equivalent disciplines is a plus
• Prior success deploying machine learning solutions in large-scale production environments
• Familiar with AWS machine learning stack
• Experience with visualization tools (e.g., Tableau, Looker Studio, PowerBI, Hex)
• Knowledge about data engineering stacks - spark, airflow or Glue

Our salary ranges are calculated by role, level and the market rate for a candidate’s geo-location. Your position within that range will be determined by your job-related knowledge, skills, experience, relevant education, and training/certifications. In addition to those factors, we also examine internal equity across the company, and title may be assessed one level lower or higher accordingly. After you join the company your performance, contributions, and results along with business and organizational needs will affect your base salary. The base salary range for this full-time position is between $163,000-$235,000 for a candidate located in the San Francisco Bay-Area. Candidates in other areas can expect local market-adjusted salaries which may be lower.

About Our Team