Engineering - Other

Fractal Analytics
Applicants0
Posted21 days ago

Job Highlights

Experience0 - 4 Yrs
Salary3-10 LPA
LocationMangalore
Work ModelHybrid
RoleEngineering - Other
Openings3
EmploymentPart-Time
EducationM.A

Required Skills

PythonJavaSQLCloud Platforms (AWS, Azure, GCP)Data Structures and AlgorithmsSoftware Development Lifecycle (SDLC)Problem-SolvingCommunication SkillsTeamworkMachine Learning FundamentalsBig Data Technologies (Spark, Hadoop)

Job Description

Role Summary:
We are seeking a highly motivated and skilled Engineer to join our dynamic team. This role will involve working on cutting-edge projects at the intersection of data, AI, and business. You will contribute to developing innovative solutions that address complex business challenges for our clients. This is an excellent opportunity for an engineer looking to grow their career in a fast-paced, analytics-driven environment.

Key Responsibilities:

  • Design, develop, and implement robust and scalable software solutions.
  • Collaborate with data scientists, analysts, and product managers to understand project requirements and translate them into technical specifications.
  • Build and maintain data pipelines, ETL processes, and data infrastructure.
  • Develop and deploy machine learning models and AI applications.
  • Write clean, efficient, and well-documented code.
  • Troubleshoot and debug issues in production and development environments.
  • Contribute to the continuous improvement of engineering practices and tools.

About Fractal Analytics

Fractal Analytics is a prominent AI and advanced analytics solutions provider, helping Fortune 500 companies make better decisions. Founded in 2010, Fractal has been at the forefront of leveraging AI, machine learning, and data science to drive business transformation across various industries. With a strong presence in India and globally, Fractal empowers organizations to unlock the power of their data, gain deeper insights, and achieve measurable business outcomes. They specialize in areas such as customer analytics, product analytics, AI engineering, and data engineering.

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