Remote - Data Scientist (Python, NLP, Statistics, ML)

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.