Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.
Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables.
Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
Analyze data for trends and patterns, and Interpret data with a clear objective in mind.
Implement analytical models into production by collaborating with software developers and machine learning engineers.
Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems.
Skills and Qualifications
Bachelor’s degree in statistics, applied mathematics, or related discipline.
7+ years’ experience in data science.
Proficiency with data mining, mathematics, and statistical analysis.
Advanced pattern recognition and predictive modeling experience.
Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (i.e., Java/Python, SAS).
Comfort working in a dynamic, research-oriented group with several ongoing concurrent projects.
Preferred Qualifications.
Master’s degree in stats, applied math, or related discipline.
Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
A successful history of manipulating, processing and extracting value from large, disconnected datasets.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Strong project management and organizational skills.
Experience supporting and working with cross-functional teams in a dynamic environment.
Skills and Qualifications
We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience with AWS cloud services: EC2, EMR, RDS, Redshift
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Design and build effective, user-friendly infrastructure, tooling, and automation to accelerate Machine Learning
Collaborate with teams to drive the ML technical roadmap
Collaborate with Machine Learning Engineers and Product Managers to develop tools to support experimentation, training and production operations
Build and maintain data pipelines using tools like Hadoop, Python, Airflow, and Kafka
Offer support and troubleshooting assistance for the ML pipeline, while continuously improving stability along the way
Build and maintain systems employing an Infrastructure-as-Code approach
Own the AWS stack which comprises all ML resources
Establish standards and practices around MLOps, including governance, compliance, and data security
Collaborate on managing ML infrastructure costs
Skills and Qualifications
3+ years of experience with ML infrastructure and ML DevOps
5+ years of overall engineering experience in distributed systems and data infrastructure
3+ years’ experience coding in Python (preferred) or other languages like Java, C#, Golang etc.
Experience working with ML engineers to build tooling and automation to support the entire ML engineering lifecycle, from experimentation to production operations
Experience with Kubernetes and ML CI/CD workflows
3+ years’ experience with AWS or other public cloud platforms (GCP, Azure, etc.)
Excellent verbal and written communication skills.
Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines are met
Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Finding available datasets online that could be used for training
Defining validation strategies
Defining the preprocessing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyperparameters
Analyzing the errors of the model and designing strategies to overcome them
Deploying models to production
Skills and Qualifications
Proficiency with a deep learning framework such as TensorFlow or Keras
Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
Expertise in visualizing and manipulating big datasets
Proficiency with OpenCV
Familiarity with Linux
Ability to select hardware to run an ML model with the required latency
Establish and implement training processes and strategies for all technical personnel
Analyze, plan and develop requirements and standards in reference to scheduled projects
Assign and oversee the daily tasks of technical personnel while ensuring all subordinates are actively working toward established milestones
Hold regular technical team meetings to determine progress and address any questions or challenges regarding projects
Determine and define clear deliverables, roles and responsibilities for staff members required for specific projects or initiatives
Research and evaluate hardware and software technology options and weigh the cost/benefit analysis when making large purchases on behalf of the company
Recruit and train exceptional employees to fulfill posted positions within the technical department
Update and maintain all production technologies ensuring proper maintenance and installation
Skills and Qualifications
Master’s degree in Project Management or related technical field required
Professional Project Management Certification from accredited intuition preferred
Demonstrated understanding of Project Management processes, strategies and methods
Experience mentoring, coaching and developing rising talent in the technology department
Excellent time management and organizational skills and experience establishing guidelines in these areas for others
Strong sense of personal accountability regarding decision-making and supervising department teams
Experience working in a high-level collaborative environment and promoting a teamwork mentality
Managerial experience applying analytical thinking and problem-solving skills
Ability to predict challenges and seek to proactively head-off obstacles
Collaborating with prospective users and clients to understand and anticipate their needs and translate them into product requirements
Defining the vision for the team’s product
Creating a product road map based on this vision
Managing the product backlog and prioritizing them based on changing requirements
Overseeing all stages of product creation including design and development
Developing user stories
Monitoring and evaluating product progress at each stage of the process
Liaising with the product team and end-users to deliver updates
Participating in Scrum meetings and product sprints
Responsible for innovation and end-to-end launch of products.
Collaborates with global commercial services partners and customers to co-develop a roadmap and drive products and features from concept to launch in a fast-paced environment.
Works with cross-functional teams and various stakeholders, including analytics, design/user experience, engineering, and user enablement.
Turns data insights into products with actionable outcomes to the ultimate customer.
Works in an Agile environment and continuously reviews the business needs, refines priorities, outlines milestones and deliverables, and identifies opportunities and risks.
Partners with stakeholders and customers across the organization to inform the product vision, strategy, features, and prioritization.
Develops, owns, and executes product roadmap.
Works with user-focused departments to define the self-service user experience, support, and monitoring for customers.
