Data Scientist (Mid-Senior)

This role supports the technical operations of Yondu HQ.

Location: YONDU HQ

Status: Active

# of Positions Available: 4

Job Description
  • Solutioning, engineering and machine learning to develop and support cloud-based AI applications and tools utilizing cutting-edge open-source and cloud technologies. This position leads and collaborates closely with quantitative analysts to understand their analytical projects and participates in all phases of the project lifecycle, including research, requirements gathering, database development, cloud-base application development, analytical report creation.
  • This role also requires the ability to explain and defend potential conclusions drawn from data, as well as the ability to identify and investigate potential data anomalies to determine root cause and recommend corrective action.
  • Display and visualize processed information so its value can be understood. Extract information from large datasets and present something of value to clients.
  • Apply exploratory or predictive analytics to solve business problems.
  • Perform data modeling. Implement and test data modeling designs. Use advanced math and statistics expertise using massive (beyond 500GB) of data. Use modern data analytical techniques working with information retrieval, machine learning, matrix and graph algorithms, unsupervised clustering & data mining to solve business problems.
  • Must be able to apply advanced analytics, predictive modeling, and data visualization skills to different business situations. Ability to work with big datasets with minimal engineering support. Demonstrate analytical and problem solving skills, particularly those that apply to a Big Data environment.
  • Ability to integrate research and best practices into problem avoidance and continuous improvement. Exercise independent judgment in methods, techniques and evaluation criteria for obtaining results.
Job Qualifications/Requirements
  • At least 3+ years (Mid), 4+ years (Senior) working with statistics 
  • Natural Language Processing: the interactions between computers and humans; 
  • Machine learning: using computers to improve as well as develop algorithms; 
  • Conceptual modelling: to be able to share and articulate modelling; 
  • Statistical analysis: to understand and work around possible limitations in models; 
  • Predictive modelling: most of the big data problems are towards being able to predict future outcomes; 
  • Hypothesis testing: being able to develop hypothesis and test them with careful experiments. 
  • Experience as a data scientist/analyst on large datasets, or data science research Worked with exploratory or predictive analytics 
  • Experience turning research ideas into actionable designs. 
  • Able to persuade stakeholders and champion effective techniques through product development. 
  • Significant experience working with Hadoop Experience in large-scale data development 
  • Experience with prediction or recommender systems, search and ranking algorithms, and classification algorithms 
  • Significant experience with machine learning 
  • Good understanding of design and architecture principles
  • Experience working with large, unfiltered data sets 
  • Strong verbal and written communication skills as well as presentation skills
  • Nice to have: Passed AWS Certified – Big Data (Specialty)