Overview of the Senior Data Scientist Position

Senior Data Scientist is responsible for working with large data sets and applying statistical, machine learning and AI techniques to solve business problems or drive the development of new data driven products. The role is expected to bring a strong stakeholder and process focus to the data science teams, the person taking up the role is expected to interface with business functions to continuously evolve the existing data products as well lead the discovery of new data driven product features. This role is also expected to manage, mentor and groom a small team of data scientists. An ideal candidate would also constantly work towards pushing the envelope of modelling techniques being used by the team.

Responsibilities

  • Work with large, complex datasets, solve hard problems using advanced statistical and Machine Learning techniques
  • Designs experiments, test hypotheses, and build models
  • Develop proof of concepts quickly and build on them iteratively to come up with production grade models
  • Enable an iterative model development process that shows value delivery and improvement to stakeholders during the development lifecycle
  • Apply advanced statistical, machine learning and predictive modelling techniques to build, maintain, and improve product features
  • Define Model Accuracy Metrics and Model testing and validation plans
  • Post production track the model performance to drive retire or retrain decisions
  • Strategic roadmap for data collection, integration and enrichment, which is in sync with the product and business strategy of the organization
  • Track the new developments in the modelling techniques, algorithms, machine learning and artificial intelligence domains.
  • Set up strong business continuity measures with respect to future model maintainability and enhancements, grooming of junior team members and setting career path expectations
  • Documentation of model wrt to modelling approach, data processing, data sources, accuracy etc
  • Set clear expectations on the team members wrt to deliverables, road map, timelines
  • Continuously mentor and manage the team members to keep them goal and process oriented

Skills & Experience

  • 3-5 years experience in working in high calibre data science teams developing production grade solutions in a dynamic environment
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, XGBoost, Neural Networks, RNN, etc
  • Preferably familiar with Big Data applications/solutions such as Hadoop, Spark, MongoDB, ElasticSearch, Kibana, etc
  • Data visualization techniques using one or more packages such Tableau, Weka or D3 visualisation.
  • Strong project and people management skills
  • Solid understanding of probability, statistics, distributions, and analysis methods.
  • Proficiency in programming languages such as Python, R, Perl, SQL and Java (Python & SQL is a must)
  • Experience with popular platforms like TensorFlow, Keras, SageMaker etc

Cultural Attributes

  • Communicator : You possess strong communication skills and enjoy working with diverse stakeholders
  • Team-Oriented: You can embrace the ideas of others (even if they conflict with your own) for the sake of the company
  • Driven: You are a driven team player, collaborator, and relationship builder whose infectious can-do attitude inspires others and encourages great performance in a fast-moving environment
  • Entrepreneurial: You thrive in a fast-paced, changing environment and you’re excited by the chance to play a large role
  • Self-motivated: You can work with a minimum of supervision and be capable of strategically prioritizing multiple tasks in a proactive manner
  • Delivery Focused: You can keep everyone focused on delivering value at the earliest.

How will your roadmap to join MoneyLion look like?

After you submit your application, you can expect the following steps in the recruitment process:

  1. Interview - Talent Acquisition Team (Virtual or face-to-face)
  2. Sample test - To be discussed in the technical round
  3. Interview - Hiring Manager (Virtual or face-to-face)