This role is responsible for analyzing and interpreting complex data sets using statistical techniques to identify trends, patterns, and insights that can be used to form business decisions and improve organizational performance. The role brings cutting edge perspective on programming techniques for data exploration, mining, preparation, cleansing, manipulation, modeling and validation. The role explores potential opportunities for improving business outcomes with data analytics and improves productivity by recommending efficient, automated processes for large scale data analyses and model development.
Responsibilities
Leads data mining using modern tools and programming languages.
Develops monitoring metrics to reflect real-world model performance and makes recommendations to shape the future direction of models and digital solutions.
Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models.
Strategizes models to uncover patterns and predictions creating business value and innovation.
Manages relationships with business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives.
Ties insights into effective visualizations communicating business value and innovation potential.
Works with development teams and business units to ensure models are scalable and can be implemented as part of the delivered solution.
Leads project team(s) of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance.
Represents the data science team for all phases of larger and more-complex development projects.
Provides guidance, training and mentoring to less experienced staff members.
Qualifications
Passion for data science & delivering data driven outcomes.
Expert knowledge of Python, SQL, and PySpark.
Experience in one or more machine learning frameworks, such as Tensorflow/Keras, PyTorch, Spark MLlib, or Scikit-Learn.
Ability to handle large amounts of structured and unstructured data and apply modern data transformation methodologies.
Extensive experience using various machine learning algorithms (e.g., classification, regression, clustering) to develop and deploy predictive models
Leads data science projects, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance.
Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models.
Ability to uncover patterns and predictions from data to create business value and innovation.
Strong analytical, problem-solving, and critical-thinking abilities.
Ability to deal with ambiguity and work collaboratively in a high paced environment.
Excellent interpersonal and project management skills; ability to work across in-person and virtual team environments.
Experience visualizing data and conveying insights in a clear and effective manner
What types of tools, software, hardware
Programming Languages: Python, SQL
Machine Learning Frameworks: Scikit-learn, Tensorflow, PyTorch, Pandas, Numpy
Data Visualization: Power BI
Preferred: Databricks, Microsoft Azure, Big Data, NLP
Education, certifications, and areas of studies
Four-year or Graduate Degree in Mathematics, Statistics, Computer Science, Data Science, or related field.
Years of experience
Typically has 7-10 years of work experience, preferably in data science, statistical modeling, machine learning, or a related field.
Knowledge & Skills
Data Science
Machine Learning/AI
Big Data
Data Mining
Deep Learning
Data Visualization
Programming Languages (Python, SQL)
Statistics
Predictive Modeling
Time-Series Forecasting
Cross-Org Skills
• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity
Impact & Scope
• Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives.
Complexity
• Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors.
Disclaimer
This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.
The base pay range for this role is $136,850 to $198,450 annually with additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only). Pay varies by work location, job-related knowledge, skills, and experience.
Benefits:
HP offers a comprehensive benefits package for this position, including:
Health insurance
Dental insurance
Vision insurance
Long term/short term disability insurance
Employee assistance program
Flexible spending account
Life insurance
Generous time off policies, including;
4-12 weeks fully paid parental leave based on tenure
11 paid holidays
Additional flexible paid vacation and sick leave (US benefits overview)
The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.