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Data Scientist
Data ScientistRedolent Infotech Pvt. Ltd. • San Bruno, CA, United States
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Data Scientist

Data Scientist

Redolent Infotech Pvt. Ltd. • San Bruno, CA, United States
[job_card.30_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

One of our direct clients is urgently looking for a Data Scientist @ San Bruno CA .

TITLE : Data Scientist

LOCATION : San Bruno, CA

Duration : 6 to 12+ Months

Description :

Role Specific Responsibilities :

  • Collaborate with the Walmart Connect Sales and Marketing teams for the development, execution, and delivery of short and long-term customer insights needs to influence media investment strategies and business growth opportunities.
  • Ensure delivery of assigned insights analyses with end-to-end ownership, clear communication, detailed project plans, and operational processes that drive visibility & accountability with Sales, Marketing & Analytics stakeholders.
  • Responsible for the development, enhancement, and production of various predictive and Machine Learning driven models to generate behavioral shopper insights, target audiences, and optimized customer journeys.
  • Drive strategic initiatives including identifying issues, creating hypotheses, executing the analysis, and translating data into meaningful insights and actions.
  • Develop and present concrete hypothesis-driven impactful deliverables clearly answering the so-what for Walmart Connect advertisers.
  • Support the development of executive-level presentations and perspectives.
  • Identify gaps and opportunities for improving existing data sources and engage with broader Walmart teams to acquire and summarize these sources within the Walmart Connect environment.
  • Support the Sales / Marketing teams in managing day-to-day operating activities and special projects.
  • Facilitate the evangelization of the team’s charters, plans, and processes across the Sales & Marketing organization.

Job Duties :

Design and build new data set processes for modeling, data mining, and production purposes. Determine new ways to improve data and search quality, and predictive capabilities. Perform and interpret data studies and product experiments concerning new data sources or new uses for existing data sources. Develop prototypes, proof of concepts, algorithms, predictive models, and custom analysis.

Minimum Qualifications :

  • PhD in Computer Science, Statistics or related field; OR a Master’s degree or equivalent in Computer Science, Statistics or related field and 2 years of related experience.
  • Knowledge of machine learning, information retrieval, data mining, statistics, NLP or related field.
  • Knowledge of one of the scripting languages such as Python or Perl.
  • Experience analyzing and interpreting the results of product experiments. Knowledge of statistical languages such as R.
  • Experience working with large data sets and distributed computing tools (Map / Reduce, Hadoop, Hive, or Spark).
  • Working knowledge of Relational Data Base Systems and SQL.
  • Experience managing end-to-end machine learning pipeline from data exploration, feature engineering, model building, performance evaluation, and online testing with big data set.
  • Excellent communications and organizational skills.
  • Prior experience in this area with eCommerce or Online Retail would be a plus.

    • Additional Requirements :

  • MUST HAVE minimum 3 years of hands-on experience of SQL in Hive / Hadoop / Google Cloud Platform environments.
  • Strong programming skills in R / Python.
  • Must have hands-on data analytics experience.
  • Practical experience in mining, analyzing and interpreting data through various statistical techniques and predictive models (e.g. Regression, Time Series, Natural Language Processing, Pattern Recognition, Classification, Segmentation, Deep Learning).
  • Must have hands-on experience with Microsoft Office Applications (e.g. Excel / PowerPoint).
  • Experience in developing and presenting strategic, action-oriented oral & written communication - providing recommendations from complex analytics efficiently and engagingly to an executive audience.

    • #J-18808-Ljbffr

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