Location: New York, San Francisco, Chicag

Employment Type: Full Time

Min. Experience: 8+ Years

Position Summary:

AbsolutData is looking for an advanced data science thinker, team leader, doer and expert who loves to dive into new and different problems, push the boundaries of innovation, and rapidly design, build and help implement machine learning and knowledge discovery solutions. Ideal candidate enjoys learning new contexts and areas of applications to help clients across industries and functions build ROI positive solutions. Creative thinking, problem solving and on-your-feet dot-connecting is very important.

Key Responsibilities:

  • Be a key component of the Big Data practice, working directly with clients to solve very important problems using internal and external data
  • Lead a consulting team of data science engineers and consultants and coordinate work on specific projects
  • Building solutions that will be applied in real time contexts, such as recommendation engines, classification and typing systems, and process management applications – using machine learning tools, near-AI processes, statistics, scripting and data integration
  • Working closely with Account Management and Business Development to design and advocate solutions

Qualifications and Skills:

  • PhD in relevant field, or Masters with substantial experience
  • 8+ years of relevant industry experience
  • Experience managing and leading a team
  • Extensive experience solving analytical problems using quantitative approaches
  • Knowledge of the standard Hadoop/MongoDB/Aster/HDFS/MapR/Hive/Pig tools
  • Excellent SQL skills; comfortable using various data access tools.
  • Good coding, scripting and prototyping skills covering some procedural as well as statistical or data oriented languages  (Such as: Java, C++, Scala, Python as well as R, SQL, etc.)
  • Experience with streaming algorithms and practical analysis of real-time data streams
  • Familiar with parallel and distributed approaches to Data Analytics and Text Mining
  • Prior experience in data mining, real-time, adaptive, probabilistic machine learning, predictive analysis, SVM, and some knowledge in NLP and text mining using Big Data
  • Expert in algorithm development & implementation
  • Statistical and predictive modeling experience
  • Experience with most of the following Machine Learning algorithms, methods, and techniques:
    • Bayesian Inference (MAP, MLE, EM, MCMC, etc.)
    • Random forest and other decision-tree algorithms
    • Social graphs, graph theory, graph theoretic inference
    • Familiarity with MATLAB, Mathematica, R, Juli, or another scientific computing language
    • Experience working with Mahout, Weka, scikit-learn, mlpy, MALLET, GSL, or other third-party machine learning tools and platforms
  • Extensive analytical toolset including an advanced understanding of statistics (time series analysis, cluster analysis, multivariate analysis), discrete simulation, linear and nonlinear optimization.
  • Experience with data analytics in the cloud
  • Familiarity with BI platforms such as Tableau and Qlikview

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