Data Scientist - AWS Job at Tekshapers Inc, Alpharetta, GA

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  • Tekshapers Inc
  • Alpharetta, GA

Job Description

Role: Data Scientist

Location: Alpharetta, GA

Duration: 6+ Months

Skills Required:

  • Experience in fraud analytics, risk management, or financial crime analytics in the banking sector with an additional emphasis on transaction monitoring
  • Machine Learning and Business Articulation

  • Expertise: Extensive experience in designing, developing, and deploying machine learning models to detect and mitigate fraud. Candidate should demonstrate a high degree of capability to translate client business statements/briefs into data-driven solutions.

  • Fintech & Fraud Detection: Background in the Fintech industry, with specific experience in financial crime and fraud detection, applying data science to solve real-world business problems.

  • Advanced Tools and Platf-orms: Experience with tools such as PySpark, Databricks, AWS, or GCP for processing large datasets, training models, and deploying them at scale.

  • Candidate must demonstrate following in their experience
  1. SME level expertise on Fraud Patterns and associated solutions
  2. Thorough knowledge of AWS ecosystem in context of AI/ML solutions
  3. Understanding Model Risk Management requirements as part of solution
  4. Excellent command of PowerPoint for creating apt business presentations

  • Expertise in AI / ML with strong focus on leveraging cloud platf-orms like AWS to build scalable, production-grade applications.

  • Strong experience with advanced SQL and good to have experience in Pyspark.

  • Good understanding or experience of working in AWS.

  • Proven track record of leading cross-functional teams to create state-of-the-art AI/ML artefacts.

"Tekshapers is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law."

Job Tags

Full time, Part time, Seasonal work,

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