Specialist - Data Science Engineer
36 Minutes ago • 8 Years +
Data Analysis
Job Description
The Specialist - Data Science Engineer applies statistical, mathematical, and predictive modeling skills to manage and manipulate high-volume data, identifying business opportunities from insights and predictions. This role involves generating algorithms, creating computer models, building web prototypes, and performing data visualization. The engineer leads data validation, strategizes new data uses, conducts scalable data research, and collaborates with engineers and scientists to translate trends into business opportunities. They also design and develop advanced AI/ML models, define ML strategy, mentor a team, and drive innovation in AI/ML methodologies.
Must Have:
- Apply and integrate statistical, mathematical, predictive modeling, and business analysis skills
- Manage and manipulate complex high volume data from various sources
- Identify business growth opportunities for Nasdaq and clients
- Generate algorithms and create computer models
- Build web prototypes and perform data visualization
- Lead data validation on hypothesis and prediction modeling activities
- Strategize new uses for data and its interaction with data design
- Conduct scalable data research and collaborate with Lead engineers and other scientists
- Collaborate with Data Engineers to develop experiments and hypothesis
- Lead statistical and mathematical predictive modeling to test hypothesis
- Work closely with business/product sponsors to understand the business needs
- Ensure hypothesis, predictive modeling, and data validation align with business opportunity
- Perform data science and machine learning activities across the Workflow and Insights Org
- Design and develop advanced AI/ML models and algorithms for complex business problems
- Define and implement ML strategy aligned with business objectives
- Lead and mentor a team of data scientists and ML engineers
- Drive innovation in AI/ML methodologies and techniques
- Establish model development, validation, and deployment standards
- Oversee model performance monitoring and optimization
- Develop frameworks for A/B testing and experimentation
Perks:
- Hybrid work model (NasdaqBlend)
- Flexibility to work from home, office, or a mix
- Total rewards program (You&Q)
- Support for building wealth
- Support for career growth
- Prioritizing well-being
- Family care
Applies and integrates statistical, mathematical, predictive modelling and business analysis skills to manage and manipulate high volume data from a variety of sources and able to identify business opportunities from the insights and predictions that result from that analysis. Collates, models, interprets and analyses data, explains variances and trends and recommends business opportunities from that analysis. Works on and off the cloud.
- Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high volume data from a variety of sources and to identify business growth opportunities for Nasdaq and their clients.
- Generates algorithms and creates computer models; builds web prototypes and performs data visualization.
- Leads data validation work on the various hypothesis and prediction modelling activities of the team; working across the team.
- Strategizes new uses for data and its interaction with data design.
- Conducts scalable data research and collaborates with Lead engineers and other scientists, discovering the trends/stories and how that translates into business opportunity.
- Collaborates with Data Engineers to develop experiments and hypothesis. Leads statistical and mathematical predictive modelling to test hypothesis.
- Works closely with business/product sponsors to understand the business needs and ensures hypothesis, predictive modelling and data validation is in line with business opportunity.
- Stays current on technological and analytical trends. Trains the data scientist team on new or updated technologies and updated procedures.
- Writes white papers for peer review
- Additionally:
- Perform the data science and machine learning activities across the Workflow and Insights Org
- Design and develop advanced AI/ML models and algorithms for complex business problems
- Define and implement ML strategy aligned with business objectives
- Lead and mentor a team of data scientists and ML engineers
- Drive innovation in AI/ML methodologies and techniques
- Establish model development, validation, and deployment standards
- Oversee model performance monitoring and optimization
- Develop frameworks for A/B testing and experimentation
- 8+ years of experience in data science/ML, with 5+ years leading teams
- PhD/Master's in Computer Science, Statistics, or related quantitative field
- Expert knowledge in machine learning algorithms and statistical modeling
- Proficiency in programming languages such as Python, R, SQL, and related ML frameworks like TensorFlow, PyTorch, and Scikit-learn
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud)
- Extensive experience with deep learning architectures
- Proven track record of deploying ML models to production
- Strong background in experimental design and causal inference
- Experience with large-scale data processing and distributed computing
Excellence in scientific writing and technical communication
Set alerts for more jobs like Specialist - Data Science Engineer
Set alerts for new jobs by Nasdaq
Set alerts for new Data Analysis jobs in India
Set alerts for new jobs in India
Set alerts for Data Analysis (Remote) jobs
