Grid Dynamics Holdings, Inc

Data Scientist
  • Job Type: Full Time
  • Industry Type: IT Sector
  • Industry Location: San Francisco
  • Experience: NA
  • No. of Positions: 1
  • Salary Range: 0-180 k
  • Primary Skills: Machine Learning Deep Learning Data Preparation NLP
  • Secondary Skills: Visualization Feature Engineering Public Cloud
  • Job Location: San Francisco, California
  • Posted Date: Posted today
Job Description
As part of the Enterprise Data team, the Data Scientist will support the development of next-generation data platforms by employing data analytics and various data science capabilities (i.e. machine learning). Incumbents will be part of an innovative and energetic team that develops capabilities which will influence our business model and help our customer build a next-generation data platform. The Data Scientist will have access to the vast amount of data stored in heterogeneous formats, is supposed to handle complex problems independently, and should demonstrate analytical thinking. Data Scientist should be able to make judgments and recommendations based on the analysis and interpretation of data.
Responsibilities:
  • Plan R&D process to fit sprint goals as well as the project milestones.
  • Design a new solution architecture for customers clusterization, NLP and prediction analysis.
  • Drive the collection, cleaning, processing and analysis of new and existing data sources.
  • Communicate with business stakeholders to clarify their requirements and present the teamwork results
Requirements:
  • Seasoned data scientist with 5+ years of experience
  • Good knowledge of the probability theory and statistics
  • Understanding of Bayesian methods, MCMC
  • Hands-on experience with probabilistic programming (Pyro, PyMC3, JAGS, or similar)
  • Experience with at least one cloud provider solution (AWS, Google Cloud Platform, Azure)
  • Experience with modeling of complex processes using Monte Carlo simulations
  • Experience with time series analysis using traditional (e.g. ARIMA) and deep learning (e.g. LSTM) methods
  • Experience with basic ML/data science libs and tools (python, scikit, NumPy, pandas, seaborn, Jupiter, etc)
  • Experience with deep learning libraries (Keras, PyTorch, TensorFlow)
  • Hands-on experience with data preparation, cleansing, feature engineering, and visualization
  • Good communication skills and interpersonal skills.
  • Experience in working across different global cultures a plus.
  • Ph.D. in Mathematics will be a plus.

What we offer:

  • Opportunity to work on bleeding-edge projects
  • Work with a highly motivated and dedicated team
  • Very competitive salary
  • Flexible schedule
  • Medical insurance
  • Benefits program
  • Corporate social events
  • Professional development opportunities

NB:

Placement and Staffing Agencies need not apply. We do not work with C2C at this time.

At this moment, we are not able to process H1B transfers.

About Us:

Grid Dynamics is a leading provider of technology consulting, agile co-creation, scalable engineering, and data science services for Fortune 500 corporations undergoing digital transformation.

We work in close collaboration with our clients on digital transformation initiatives that span strategy consulting, early prototypes, and enterprise-scale delivery of new digital platforms. We help organizations become more agile and create innovative digital products and experiences using deep expertise in emerging technology, top global engineering talent, lean software development practices, and high-performance product culture.

Headquartered in Silicon Valley with over 1,300 technologists located in engineering delivery centers throughout the US, Central, and Eastern Europe, Grid Dynamics has architected and delivered some of the most extensive digital transformation programs in the retail, technology and financial sectors to help its clients win market share, shorten time to market and reduce costs of digital operations on a massive scale.

To learn more about Grid Dynamics, visit www.griddynamics.com, or follow us on Twitter @GridDynamics.

 

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