Data & AI Specialist


Your responsibilities will include:

Bringing the State of the Art to Products

  • Participates in collaborative relationships with relevant product and business groups inside or outside of Polser and provides expertise or technology to create business impact.
  • Collaborates with and bridges the gap between researchers and development teams. Brings new technology and approaches into production by applying long-term research efforts to solve immediate product needs.
  • With limited guidance from others, works to create product impact. Identifies approach, and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact a Polser product or service. Solves components or aspects of a problem as assigned by a trusted team member. May publish research to promote receiving new intellectual property for product impact.


Leveraging Applied Research

  • Gains expertise in one or more subareas of research (e.g., Object Recognition, Text Classification), gains understanding of a broad area of research (e.g., Machine Learning, Natural Language Processing, Computer Vision, Statistical Modeling, Data-Driven Insights), and understands the corresponding literature and applicable research techniques. Uses understanding of approaches to identify techniques and seeks feedback from team members.
  • Gains deep knowledge in a service, platform, or domain and acquires knowledge of changes in industry trends and advances in applied technologies. Consults with engineers and product teams to apply advanced concepts to product needs. Learns product domain by reviewing products.
  • Applies strategy by understanding the role in the team and applying the strategy provided by team members and incorporates state-of-the-art research. Asks probing questions to better understand strategy.
  • Researches and develops an understanding of tools, technologies, and methods being used in the community that can be utilized to improve product quality, performance, or efficiency. Contributes knowledge around several specialized tools/methods to support the application of business impact or serves as a dependable resource in a deeply specialized area.


Capability Management and Networking

  • Reinforces a positive environment by applying best practices. May support mentorship by assisting with onboarding of research interns or other entry-level team members, if applicable.
  • Maintains ties with external network of peers and identifies prospective talent, when asked. May contribute to publications on research findings. May participate in candidate interviews. Collaborates with the academic community to develop the recruiting pipeline and establish awareness of their work.



  • Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Participates in the creation of informal documentation and may share findings to promote innovation within group.


Ethics and Privacy

  • Understands and follows ethics and privacy policies when executing research processes and/or collecting data/information.


Specialty Responsibilities

  • Prepares data to be used for analysis by reviewing criteria that reflect quality and technical constraints. Reviews data and suggests data to be included and excluded. Describes actions taken to address data quality problems. Assists with the development of useable datasets for modeling purposes. Supports the scaling of feature ideation and data preparation. Helps take cleaned data and adapts for machine learning purposes, under the direction of a trusted team member. Seeks guidance from trusted team members when confronted with problems/challenges.*
  • Leverages or designs and uses machine learning/data extraction, transformation, and loading (ETL) of pipelines (e.g., data collection, cleaning) based on data prepared.*
  • Collaborates to leverage data to identify pockets of opportunity to apply state-of-the-art algorithms to improve a solution to a business problem. Uses statistical analysis tools for evaluating Machine Learning models and validating assumptions about the data while also reviewing consistency against other sources. Begins to independently run basic descriptive, diagnostic, predictive, and prescriptive statistics. Assists with the communication of insights under the direction of trusted team members.*
  • Uses machine learning algorithms that structures, analyzes, and uses data in product and platforms to train algorithms for scalable artificial intelligence solutions before deploying. Begins to develop new machine learning improvements independently while under the direction of a reliable team member.*
  • Supports the application and use of intelligence created during the training of algorithms for deployment. Seeks information about large-scale computing frameworks, data analysis systems, and modeling environments to improve models. Helps create a model, apply the model to real products, and then verify effects through iterations. Helps with experiments by putting multiple models in production and evaluating their performance. Sets up monitoring and implementation to track production models, under the direction of a trusted team member. Addresses models when that break, under the direction of others.*



Required/Minimum Qualifications:

  • Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
    • OR equivalent experience.
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