ShyftLabs
ShyftLabs
ShyftLabs кәсіпорындарға деректер мен жасанды интеллектіні іс жүзінде қолданылатын бизнес мүмкіндіктеріне айналдыруға көмектеседі. Компанияның қызметі деректер мен жасанды интеллект бойынша консалтингті, жедел прототип жасауды, шешімдерді іске асыруды, платформаларды ауқымдауды және үздіксіз операцияларды қамтиды. Осылайша ұйымдарға бастапқы стратегия әзірлеуден бастап өндірістік ортаға енгізуге дейін қолдау көрсетіледі. Компания қолданыстағы жұмыс үдерістерімен ықпалдасуға және операциялық тиімділікті арттыруға бағытталған қауіпсіз деректер инфрақұрылымын, бұлтты платформа қызметтерін, аналитика мен жасанды интеллект шешімдерін әзірлейді. ShyftLabs деректер мен жасанды интеллект бастамаларының бүкіл өмірлік циклі бойында клиенттермен серіктесіп, енгізу жұмыстарын олардың трансформация мақсаттарына бейімдейді.

Data Scientist (Hybrid, India)

ShyftLabs is seeking a Data Scientist to develop predictive models, run experiments, and build data pipelines. The role turns complex analysis into recommendations that inform product and business decisions.

Сипаттама

  • Develop and validate machine learning models for forecasting, segmentation, and recommendations
  • Work with product and engineering teams to frame business questions as analytical problems
  • Explore and analyze large datasets to identify meaningful patterns
  • Plan and assess A/B tests and other experiments
  • Create and maintain data pipelines in collaboration with data engineering
  • Present insights through reports, dashboards, and presentations
  • Track deployed model performance and drift, improving models when needed
  • Help establish strong practices for experimentation, model evaluation, and data quality
  • Transform company data into actionable insights and intelligent products

Талаптар

  • At least three years of experience in data science, applied machine learning, or quantitative analytics
  • Advanced working knowledge of Python, including Pandas, NumPy, and Scikit-learn, plus SQL
  • Strong understanding of statistics and experiment design, including A/B testing
  • Practical experience developing and evaluating machine learning models for real-world applications
  • Clear communication skills for explaining technical results to non-technical audiences
  • Experience handling large datasets and producing efficient, production-ready analysis code
  • Familiarity with Matplotlib, Seaborn, Tableau, or comparable data visualization tools
  • Python
  • Pandas
  • NumPy
  • Scikit-learn
  • SQL
  • Statistics and experiment design, including A/B testing
  • Machine learning model development

Артықшылықтар

  • Competitive compensation with performance-based bonuses
  • Flexible working hours with remote and hybrid work options
  • Health insurance and wellness benefits
  • Budget for learning and professional development
  • Collaborative setting where analytical work directly informs decisions

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