Data Scientist

1 Month ago • 5 Years + • Artificial Intelligence

About the job

Job Description

ShyftLabs seeks an experienced Data Scientist to improve product performance and cost efficiency using ML/AI and infra systems. Responsibilities include researching, designing, and developing generative AI models; collaborating with cross-functional teams on AI solutions; training and optimizing AI models; staying current on AI advancements; ensuring data quality; designing and implementing machine learning algorithms; developing and maintaining AI infrastructure; documenting processes; and integrating AI/ML models into applications. The ideal candidate will have a strong understanding of statistics, machine learning algorithms, and programming (Python, SQL).
Must have:
  • Master's degree in quantitative discipline
  • 5+ years experience
  • Strong statistical knowledge
  • Deep understanding of ML algorithms
  • Proficiency in Python & SQL
Perks:
  • Competitive salary
  • Strong insurance package
  • Extensive learning & development resources

About the job

Position Overview

Here at ShyftLabs, we are searching for an experienced Data Scientist who can derive performance improvement and cost efficiency in our product through a deep understanding of the ML/AI and infra system, and provide a data driven insight and scientific solution.

ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.

Job Responsibilities

  • Research, design, and develop innovative generative AI models and applications.
  • Collaborate with cross-functional teams to identify opportunities for AI-driven solutions.
  • Train and fine-tune AI models on large datasets to achieve optimal performance.
  • Optimize AI models for deployment in production environments.
  • Stay up-to-date with the latest advancements in AI and machine learning.
  • Collaborate with data scientists and engineers to ensure data quality and accessibility.
  • Design, implement, and optimize machine learning algorithms for tasks like classification, prediction, and clustering.
  • Develop and maintain robust AI infrastructure.
  • Document technical designs, decisions, and processes, and communicate progress and results to stakeholders.
  • Work with cross-functional teams to integrate AI/ML models into production-level applications.

Basic Qualifications

  • Master's degree in a quantitative discipline or equivalent.
  • 5+ years minimum professional experience.
  • Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets, and using statistics to arrive at a recommendation.
  • Excellent verbal and written communication skills, with the ability to present information and analysis results effectively.
  • Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company.
  • Statistics : must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques.
  • Machine Learning : must have a deep understanding of ML algorithms (i.e., deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and their development, validation, and evaluation.
  • Programming : experience with Python in relevant libraries(ex - SKlearn, pandas, LangChain, etc) and SQL.

We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

PI255074359

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About The Company

Here at ShyftLabs, we build data products to help enterprises deliver real impact through tailored data analytics, science, and AI solutions. From consulting to operations, we guide our customers through their data journey and ensure they are data and AI-empowered.

Uttar Pradesh, India (On-Site)

Noida, Uttar Pradesh, India (Hybrid)

Hyderabad, Telangana, India (On-Site)

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