At PitchBook we work to provide global professionals with comprehensive data on the entire venture capital, private equity and M&A landscape so they can discover and execute opportunities with confidence. We credit our success and rapid growth to our cutting-edge products, customer centered attitude and ability to embrace and drive change.
In just over a decade, PitchBook has reached over 3,500 people with offices worldwide, and we're not slowing down! Consistently recognized as a Best Place to Work, our culture is at the heart of our success and is driven by excellence, inclusion and fun. At PitchBook we're committed to fostering an open and collaborative work environment.
About the Role: 
As the Machine Learning Engineering Manager in PitchBook's engineering division, you will be leading machine learning, data science and applied mathematics engineering activities for PitchBook globally. You will work closely with colleagues to build optimal solutions to complex challenges, engaging our machine learning engineers, data scientists and data engineers to unearth innovative ways to apply modern technologies and tools to delight our customers with the value of PitchBook data.
Your target will be to drive value for our customers through the speed, quantity, quality and discoverability of data in the PitchBook platform using machine learning technologies and data algorithms. Incorporated in this are both the ability to decipher insights from millions of discrete unstructured and structured data sources for incorporation in our platform and the acumen to apply machine learning models to our stored datasets to deliver unique insights and predictions to our customers.
You will utilize your strong background in data analysis, annotation, natural language processing and understanding (NLP/NLU), machine learning model development, algorithms development, statistics and software engineering to help organize, manage and grow our AI/ML efforts. You will facilitate strong decision-making, learning-oriented and iterative scientific processes, collaboration across teams and the career growth and development of our ML and data science team members. You will dive deep into our data algorithms, machine learning models and data engineering code frequently, overseeing that our techniques, technologies and applications meet or exceed our high standards. You will drive efficiency into our processes by owning our ML Ops pipelines and ensuring we have aligned, integrated and effective tooling.
Your ability to collaborate with product management, provide leadership across multiple locations, set a high bar for our team members and hire, train and retain exceptional talent in the organization will be critical to your success. You will solicit feedback, engage others with empathy and help create a culture of belonging, teamwork and purpose. 
Primary Job Responsibilities:

• Lead machine learning engineering and data science technical direction and execution (operations, processes, practices and standards) and code quality across the organization, working closely with engineering leadership and product management to craft roadmaps and achieve success criteria 
• Bridge the gap between business/product needs and execution, including building and delivering on group-level OKRs, identifying resource needs, building execution plans for initiatives, making smart tradeoffs and owning the answers to "how?", "how much?", "who?" and "when?" for machine learning engineering
• Ensure machine learning roadmap items are delivered on time and with exceptional quality
• Extend influence across distributed machine learning teams to make strong day-to-day decisions independently through effective knowledge management, communities-of-practice, mentorship and training
• Serve as a force multiplier for machine learning teams by removing roadblocks, identifying and implementing process improvements, providing frequent, actionable and constructive feedback to team members and building practices for ideation and innovation
• Ensure robust machine learning engineering diagrams are maintained, developing a detailed understanding of key aspects of the current software state and engaging machine learning engineers at a code and design level
• Describe technical context in intuitive ways for different audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders
• Learn constantly, including NLP techniques, machine learning technologies, libraries and frameworks (commercial and open-source), data engineering, cloud services for machine learning (i.e. SaaS/PaaS offerings) and machine learning operation tools
• Establish and drive a culture founded in creating belonging, psychological safety, candor, connection, cooperation and fun
• Understand how to apply Agile, Lean and principles of fast flow to team efficiency and productivity

Skills and Qualifications:

• M.S. in Computer Science, Data Science, Machine Learning, Software Engineering or related
• 7+ years in engineering or data science roles with a machine learning focus
• 3+ years in an engineering leadership role with direct management responsibilities of at least 5 people
• 3+ years of hands-on coding and delivering large-scale machine learning models and systems as a Machine Learning Engineer or Data Scientist. Natural language processing (NLP) experience is a must
• Extensive experience with Python and associated machine learning libraries such as pandas, scikit-learn, keras and PyTorch
• Strong SQL knowledge is a must
• Experience owning machine learning services that are provided "as a service" to other teams as part of a large-scale distributed microservices architecture
• Experience with data pipelining, data platform and data lake/warehouse technologies, such as Apache Kafka, Amazon SNS/SQS/Kinesis, Apache Airflow, Spark, AWS Glue, GCP Cloud Dataflow and Snowflake
• Experience with containerization technologies, including Kubernetes and Docker and understanding how to build for cloud-scale delivery, including scalability, resiliency and recoverability
• Experience with Java, Spring Framework (including Spring Boot) and Java-oriented middleware technologies are a plus
• Have successfully created and executed multi-year technical initiatives, with a strong metrics focus
• Excellent communication skills, written and verbal. You're a polished presenter. You can effectively read the situation and adjust your communication style to the audience

If you are ready to start the conversation about how you might contribute to all the happenings at PitchBook, submit your resume today! PitchBook appreciates and respects diversity, and as such, we are an equal opportunity employer.
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