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Manager Recommender Systems Jobs in Missouri (NOW HIRING)

Attract, retain, develop, manage, coach and assess data scientists in a balanced team * Work with ... Build and optimize recommendation and ranking systems balancing relevance, discovery, and business ...

Role The Senior Product Manager - Recommendations & AI will lead the evolution of our e-commerce ... Lead the development and optimization of AI-driven recommendation systems, leveraging generative AI ...

Monitor industry trends, new features, and product roadmaps to recommend and plan system ... Support sales and business development teams in managing opportunity pipelines, customer and ...

Practice Manager

Saint Louis, MO · On-site

$55K - $65K/yr

Oversee and manage all day-to-day administrative and operational functions of the practice ... Train staff on EHR workflows; identify inefficiencies and recommend system improvements Required

Practice Manager

Saint Louis, MO · On-site

$55K - $65K/yr

Oversee and manage all day-to-day administrative and operational functions of the practice ... Train staff on EHR workflows; identify inefficiencies and recommend system improvements Required

Manage Active Directory, Group Policy, DNS, DHCP, and related domain services. * Maintain ... Evaluate emerging technologies and recommend improvements that increase reliability, security ...

This role provides technical expertise across servers, virtualization, storage, identity management ... recommend improvements that increase reliability, security, efficiency, and business value ...

Project Manager

Joplin, MO · On-site

$125K/yr

... and recommend systems, programs, or policy improvements. * Experience analyzing business and ... with managers, executives, technical officials, and other stakeholders to resolve implementation ...

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Showing results 1-20

Manager Recommender Systems information

What is a manager recommender systems?

A Manager of Recommender Systems is a professional who oversees the development and deployment of algorithms that suggest products, services, or content to users based on their preferences and behavior. They lead teams of data scientists, engineers, and analysts to design, implement, and optimize recommendation engines. Their role involves strategic planning, project management, and ensuring that the recommender systems align with business goals while delivering a personalized user experience.

What are the key skills and qualifications needed to thrive as a manager recommender systems?

To thrive as a Manager, Recommender Systems, you need a solid background in computer science, machine learning, and data analytics, typically supported by a relevant degree and experience in building recommendation algorithms. Familiarity with programming languages like Python or Scala, machine learning frameworks, and big data platforms such as Spark or Hadoop is essential, along with knowledge of A/B testing and model evaluation techniques. Strong leadership, project management, and cross-functional communication skills distinguish top performers in this role. These skills ensure effective team guidance, robust system development, and alignment of technical solutions with business goals in a fast-evolving digital landscape.

How does a manager recommender systems typically collaborate with data scientists and engineers to deliver effective recommendation solutions?

As a Manager of Recommender Systems, you will frequently coordinate cross-functional efforts between data scientists, machine learning engineers, and product teams. Your role involves setting project priorities, facilitating communication to ensure clear understanding of objectives, and removing roadblocks that may impede progress. You’ll also oversee the translation of business requirements into technical solutions, review algorithm performance, and guide the team in iterative model improvements. Regular collaboration ensures that the recommendations delivered align with both user needs and business goals.

What is the difference between Manager Recommender Systems vs Data Scientist?

AspectManager Recommender SystemsData Scientist
CredentialsAdvanced degree in CS, ML, or related field; experience with recommender algorithmsDegree in CS, Statistics, or related; strong programming and analytical skills
Work EnvironmentLeading teams, overseeing recommender system projects, collaborating with product teamsAnalyzing data, building models, interpreting results across various domains
Industry UsageTech companies, e-commerce, streaming services

While both roles require strong technical skills and data expertise, Manager Recommender Systems focus on leading teams and managing recommender system projects, whereas Data Scientists primarily analyze data and develop models across diverse applications.

What are the most commonly searched types of Recommender Systems jobs in Missouri?

The most popular types of Recommender Systems jobs in Missouri are:

What are popular job titles related to Manager Recommender Systems jobs in Missouri?

For Manager Recommender Systems jobs in Missouri, the most frequently searched job titles are:

Manager, Data Science (Personalization & Recommendation Systems) (Remote)

Kohl's

On-site

Full-time

Posted 29 days ago


Kohl's rating

5.8

Company rating: 5.8 out of 10

Based on 1,480 frontline employees who took The Breakroom Quiz

12th of 21 rated department stores


Job description

Role Specific Information

Job Description

About the Role

As Manager, Data Science, you will manage a data science team and work with cross-functional partners to solve business challenges and promote data-driven decision-making with advanced data analysis and machine learning.


What You'll Do

  • Attract, retain, develop, manage, coach and assess data scientists in a balanced team

  • Work with product, engineering and design leads and leverage data-driven insights to make decisions, set goals, prioritize work and achieve team objectives

  • Lead end-to-end data science projects from problem formulation to model deployment, ensuring high-quality deliverables that meet business needs

  • Oversee the design of experiments that answer targeted questions

  • Identify and drive continuous improvement of key business metrics within assigned team

  • Translate data science outputs into business outcomes and value delivered

  • Maintain strong business partner relationships to gain cross-organizational alignment, spur adoption and usage of data science capabilities and drive business outcomes

  • Remain current on the latest trends and developments in data science and technology and identify areas that offer the greatest return on investment

  • Additional tasks may be assigned

Addendum

Personalization & Recommendation Systems

Accountabilities

  • Design and support deployment of machine learning models to power personalized experiences across digital channels (e.g., homepage, PDP, cart, campaigns)

  • Build and optimize recommendation and ranking systems balancing relevance, discovery, and business objectives (e.g., conversion, revenue)

  • Develop multi-stage ranking approaches, including candidate generation and re-ranking

  • Address cold-start and long-tail challenges in large product catalogs

  • Partner with engineering to support real-time personalization and scalable deployment

Skills & Experience

  • Experience with personalization & recommendation systems, search, or ranking problems at scale of millions of customers and products

  • Experience in developing sequential, transformer models and utilizing LLM models in production

  • Understanding of collaborative filtering and learning-to-rank methods

  • Experience optimizing models for GPU / distributed training

  • Familiarity with large-scale datasets and production ML systems

  • Exposure to real-time or low-latency serving environments

  • Experience with vector search / ANN methods (e.g., FAISS, ScaNN) preferred

  • Experience with delivering end to end customized ML models in production environment

Required

  • Expertise in developing and deploying state-of-the-art algorithms using machine learning and statistical and optimization methods to power various aspects of highly complex business models and deliver value

  • Expert in using modern analytics tools, programming languages, and cloud platforms such as Python, R, Spark, SQL, GCP, etc.

  • Strong problem-solving skills with an emphasis on product development

  • Experience proposing rapid experiments to test the efficacy of new strategies or initiatives and iterating quickly based on results

  • Proven success guiding teams through unstructured technical problems

  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or equivalent quantitative field

  • 5+ years (or 2+ years with a Master's degree) of progressively complex data science experience

  • 2+ years of managerial or leadership experience in data science or analytics organizations

Preferred

  • Master's degree and/or Ph.D.

  • Retail experience

  • Marketing models

Essential Functions

The requirements listed below are representative of functions you will be required to perform, however you may be required to perform additional functions. Kohl's may revise this job description at any time. To perform this job successfully, you must be able to perform each essential function satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions, absent undue hardship.

  • Ability to perform the accountabilities listed in the "What You'll Do" Section

  • Ability to comply with dress code requirements

  • Basic math and reading skills, legible handwriting, and basic computer operation

  • Ability to maintain prompt and regular attendance and meet scheduling requirements as set by the company

  • Ability to learn and comply with all company policies, procedures, standards and guidelines

  • Ability to give direction and to receive, understand and proactively respond to direction from leadership and other company personnel

  • Ability to work as part of a team and interact effectively and appropriately with others

  • Ability to maintain composure and work in a fast paced environment while accomplishing multiple tasks within established timeframes

  • Ability to satisfactorily complete company training programs

  • Ability to use a personal computer for tasks such as communicating, preparing reports, etc.

  • Ability to plan, prioritize and monitor activities across business units

  • Ability to complete or oversee the completion of assigned projects in a timely manner


What Kohl's employees say

Pay

Benefits

Hours and flexibility

Workplace

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