Job Description :

Title: Data Scientist (Python, NLP, Statistics, ML)

Roles & Responsibilities

  • Apply statistics, mathematics, data science, machine learning techniques and solutions meet software requirements.
  • Design and implement machine learning architecture and methods per client’s requirement.
  • Enhance and maintain current analysis tools, including automation of current processes using AI/ML algorithms.
  • Build supervised and un-supervised models for risk prediction, anomaly detection and timeseries analysis.
  • Conduct quantitative data analysis using a variety of large structured and unstructured datasets, including developing retrieval, processing, fusion, analysis, and visualization of various datasets.
  • Identify and test hypotheses, ensuring statistical significance, as part of building predictive models for business application.
  • Translate quantitative analysis, findings into accessible visuals for non-technical audiences, and provide a clear view into data interpretation.
  • Enable business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes.
  • Maintain understanding of strategic goals, business challenges and customer needs.
  • Write clean scripts for data analysis, ETL, and visualization.
  • Prepare and present findings of investigations & solutions to stakeholder.
  • Help your team understand use of various analytics/statical/ machine learning tools and methods.
  • Bring your curiosity, innovative spirit, and passion to deliver on the promise of technology in a difficult, competitive, and exciting vertical.


Required Qualifications  & Experience:

  • Master’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, Applied Statistics, or related field.
  • Experience 3+ years with machine learning in industry environment.
  • Experience 5+ years coding in Python, Scala, or similar.
  • Advanced understanding of probability, statistics, machine learning, data science.
  • Expertise in data correlation/feature analysis, analysis of machine learning models, and optimizing models for accuracy.
  • Proficiency in transforming and cleaning data & working across multiple models.
  • Ability to research and manipulate complex and large data sets (both distributed and non-distributed).
  • Strong fundamentals in problem solving, algorithm design, and model building.
  • Ability to solve complex business problem through logical and creative thinking.
  • Strong ability to synthesize complex information.
  • Excellent Code writing capability in Python  and familiarity with relevant ML packages.
  • Familiarity with libraries such as Pandas, Scikit-learn etc.
  • Experience of working on Fraud detection solution.
  • Excellent knowledge of anomalies/outliers detection using unsupervised algorithms – clustering, Local Outlier Factor, Isolation Forest , etc.
  • Deep learning experience would be added advantage.
  • Experience with Spark DataBricks frameworks.
  • Interest in applying data science in the fields of compliance.
  • Strong written and verbal communication skills.



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