Overview
Machine Learning Managers manage the work efforts of Machine Learning Scientists and are accountable for the performance and results of their staff. They oversee highly complex projects that have significant impact on the organization. They consult on complex issues and contribute key ideas.
They are a spokesperson and advocate on relevant machine learning topics to both internal and external audiences and stakeholders. They contribute directly to the features and capabilities deployed in our applications. They are responsible for advanced project delivery, execution, and support.
They work closely with cross-functional business units, software engineering, and data scientists to simulate and test econometric/probabilistic relationships across the big data stack. They also work with product and marketing teams to understand client goals and turn research into products. Machine Learning Managers provide guidance to their staff within the latitude of established company policies and receive assignments in the form of objectives and determine how to use resources to meet schedules and goals.
They adapt departmental plans and priorities to address resource and operational challenges. They have responsibility for human resources related activities, such as hiring, performance management, career development, pay reviews, etc. They participate in the budget process, as well as forecasts for their department. Machine Learning Managers have extensive knowledge of the field and possess a combination of machine learning, computer science, data mining, and statistical experience.
They demonstrate strong leadership skills and create an atmosphere that encourages and fosters superior teamwork and strong work ethics.
Company:
DST Applied Analytics
Qualifications:
Desired Skills and Experience
Technical Qualities
Demonstrate ability to build, analyze, and troubleshoot our proprietary targeting and analytic system to optimize revenue across multiple business units. Analyze and extract relevant information from large amounts of business data and translate learning’s from data insights into system concepts and computer algorithms that form core analytic products.
Serve as a primary person to consult on complex issues and contribute key ideas. Be a spokesperson and advocate on relevant machine learning topics to both internal and external audiences and stakeholders. Work closely with cross-functional business units, software engineering, and data scientists to simulate and test econometric/probabilistic relationships across our big data stack. Work with product and marketing teams to understand client goals and turn research into products.
Input into scope of new algorithm development; including design of algorithms and building of models and software in order to optimize key business metrics; analyze the performance of individual algorithms and collections of multiple algorithms; and develop techniques for monitoring and visualizing the performance of all deployed algorithms.
Assist in conducting proof-of-concept studies for early stage research. Input into research and implementation of new, distributed, and scalable machine learning and statistical approaches. The role is responsible for managing and supporting advanced project delivery, execution, and support; and to also understand and affect product directions. The role will need to demonstrate a combination of machine learning, computer science, data mining, and statistical experience.
They also mentor and develop team members as well as other technical roles when needed. They have extensive knowledge of the field and work on highly complex projects that have significant impact on the organization.
Education/Training
Minimal Qualifications: Bachelor’s degree in Computer Science or related field (Statistics, Mathematics, Engineering) or equivalent combination of education plus work experience; 2 years’ industry experience maintaining a code base written in a high-level object-oriented language; formal studies or industry experience in distributed computing (e.g., MapReduce, Hadoop, AWS, DHTs, etc.); industry experience working with very large datasets; familiarity with parallel programming or parallel algorithms development; familiarity with machine learning concepts, data mining, knowledge discovery, and information retrieval (NLP & Semantic Analysis); strong background in Math, Statistics, and Engineering concepts; demonstrated leadership attributes.
Optimal Qualifications: Masters or PhD in Computer Science or related field (Statistics, Mathematics, Engineering); 2+ years’ industry experience maintaining a code base written in a high-level object-oriented language; industry experience in distributed computing (e.g., MapReduce, Hadoop, AWS, DHTs, etc.); industry experience working with very large datasets; experience with parallel programming or parallel algorithms development; experience with machine learning concepts, data mining, knowledge discovery, and information retrieval (NLP & Semantic Analysis); strong background in Math, Statistics, and Engineering concepts; experience with Graph Analysis, Recommender Systems (Collaborative Filtering), and probabilistic algorithms; staff supervisory or management experience.
Educational level:
Master Degree
Level of experience (years):
Mid Career (2+ years of experience)
How to apply:
Please mention NLP People as a source when applying
