The core of Quant is Data Science, and hence it requires highly capable individuals that can deliver the level of quality our clients have grown accustomed to, and to have a mindset that’s highly agile, critical and curious. The Senior Data Scientist is required to collect, analyze and interpret large data sets in order to develop data-driven solutions, insights, and visualizations for difficult business challenges.

Job Responsibilities:

• Collaborate with executive stakeholders to understand strategic needs and challenges through data, devising sophisticated solutions to drive business impact.
  

• Lead the mining and analysis of data from various databases, ensuring alignment with organizational objectives to derive actionable optimization recommendations.
  

• Research, develop, and implement advanced statistical learning models for in-depth data analysis and predictive insights.
  

• Introduce and integrate cutting-edge statistical and mathematical methodologies as required for specific projects and analysis.
  

• Optimize collaborative development efforts through strategic database utilization and robust project design.
  

• Enhance data collection procedures to ensure the inclusion of comprehensive information critical for advanced analytic systems.
  

• Develop and maintain automated anomaly detection systems, ensuring rigorous performance monitoring and improvement.
  

• Writing comprehensive reports and crafting high-level presentations that clearly communicate project deliverables, findings, and strategic recommendations to key decision makers.
  

• Integrate external third-party data sources to enrich company data and augment analytical capabilities.
  

• Stay abreast of emerging technologies and industry trends, driving continuous innovation within the data science team.
  

Requirements

Skills Required:

• A minimum of four years of comprehensive experience in data science, including demonstrated success in leading projects.
  

• Strong proficiency in Python programming and data science frameworks such as scikit-learn, pandas, numpy, scipy etc.
  

• Work experience in deep learning frameworks such as Pytorch, Tensorflow, Keras, etc.
  

• Has a strong understanding of the fundamentals of machine learning, probability and statistics and algorithms.
  

• Proficiency in SQL and experience with relational databases.
  

• Experience in data visualization tools such Matplotlib, Seaborn, Tableau and/or Power BI.
  

• Excellent problem-solving and analytical abilities and attention to details.
  

• Good grasp of data engineering and devOps concepts and tools and the best practices of software development.
  

Skills Preferred:

• Experience in working in geospatial data analytics and time series forecasting.
  

• Familiarity with big data frameworks like Hadoop or Spark.
  

• Experience in computer vision libraries and frameworks such as OpenCV, scikit-image, or SimpleCV.
  

• Familiarity with advanced computer vision techniques such as object detection, image segmentation, and facial recognition.
  

• Understanding of NLP, graph neural networks and reinforcement learning fundamentals.