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Data Scientist - Remote

Roles & Responsibilities

  • Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics or relevant fields (Advanced Degree Preferred)
  • 3+ years of relevant experience
  • Significant prior success as a Data Scientist (2+ years) working on challenging problems at scale
  • In-depth knowledge of machine learning methods (regression, NLP, time series forecasting) and full-stack data science lifecycle

Requirements:

  • Lead end-to-end delivery of large-scale cross-functional analytics projects leveraging technologies such as Python, SQL, Spark, and related tools; develop statistical and machine learning models and communicate insights to executives
  • Oversee building and deploying complex ML models through all phases (design, training, evaluation, validation, implementation) and coordinate with Model Risk Governance and Compliance for approvals
  • Ensure models solve business problems, are moved to production efficiently, and are integrated into downstream processes (marketing, fraud detection, pricing, network tactics)
  • Build and maintain relationships with strategic partners and provide data discovery, target definition, and technical support while ensuring compliance; synthesize partner experience for the AMCB DA team

Job description


Data Scientist I
Location: Remtoe
Duration: 6+ months

Job description:

The incumbent develops predictive and prescriptive analytics for a variety of strategic business challenges in consumer, commercial and shared services at Client. The incumbent will be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records. The incumbent oversees the development of statistical and machine learning models, data mining and advanced analytic solutions, and facilitates key strategic discussions and provide thought leadership to executive audience.
Leading end-to-end project delivery for large scale and cross-functional advanced analytics projects leveraging advanced technologies (Python, SQL, Java, Cortex, PySpark, ArcPro, Distributed Computing) and methods (advanced statistics, advanced mathematics, machine learning, geospatial analytics, Storytelling & visualization). Engaging and communicating with senior executives, and business partners from the start and through the journey, crafting and articulating the business problems from a technical/quantitative definition and facilitate key strategic discussions and provide thought leadership.

Lead and oversee building best-in-class complex statistical and machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. Lead effective interaction with Model Risk Governance(MRGM) and Compliance(CAP) partners in order to successfully go through approval and validation process in a timely manner.
Ensure that the model/project solves the desired business problem, is moved to production efficiently, and is deployed for maximum value and work with downstream teams as a model expert, integrating the model output to maximum effectiveness (e.g. in marketing campaigns/fraud detection/pricing optimization/network tactics etc.).
Build and maintain relationship with our strategic partners (L6, AMCB teams, ED&A, and external consultants) and ensure that their solution solves the desired business problem, is moved to production efficiently, and is deployed for maximum value. Support our strategic partners with data discovery, target definition and other technical support, and collaborate with them to satisfy control & compliance partner requirements. Bring their experience back to the AMCB D&A team.

Job Requirements
Develop robust and reliable machine learning algorithms helping to solve strategic business challenges
Use modern machine learning techniques on structured and unstructured data
Leverage a broad stack of technologies Python, Conda, Azure DataBricks, Java, Spark, and more to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Communicate model algorithms and results to senior leaders and business partners
R&D on new Machine Learning techniques and their applications
Strategic partner to leadership team on the management of the portfolio and financials, with deep industry, external / internal, enterprise knowledge, recognizing and anticipating emerging trends and; identifying operational efficiencies and opportunities with other business management / enterprise areas
Focus on longer-range planning for functional area (e.g. 12 months or greater)

Qualifications
Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics or relevant fields (Advanced Degree Preferred)
3 + years relevant experience
Significant prior success as a Data Scientist (2+ years) working on challenging problems at scale
In-depth knowledge of regressions such as logistic regression, supervised and unsupervised machine learning algorithms such as Gradient Boosting Method, XGBoost, NLP, Spatial DataScience etc., and time series forecasting
Have full stack experience in data collection, aggregation, analysis, visualization, productionization, and monitoring of Data Science products
Good understanding of object oriented programming, testing framework and proficiency in programming languages such as R, Python and libraries/modules such as pyspark, sklearn, pytest, etc.. Familiarity with functional programming in Java, ArcGIS is a plus.
Working experience in the knowledge and utilization of Cloud platforms (AWS, Azure or Google Cloud).
Experience with both spark/HDFS system and traditional relational database/system language(e.g. SQL, etc.)
Familiarity with version control software or platform such as Git, Bitbucket or Github; IDE such as PyCharm, IntelliJ or Visual Studio Code.
Strong analytical and program solving skills are required to interpret data and draw conclusions.
Excellent written and verbal communications skills.
Ability to provide conflict resolution.

Strong ability to successfully balance competing priorities in a fast-paced environment

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