Lead Data Scientist at Reston, Virginia (Initial Remote)

KMM an ISO 9001:2015, CMMI Level 2 certified company provides high-quality IT consulting services and innovative solutions by using the most effective and modern technologies. We have a core group of Subject Matter Experts with certifications and immense experience in successfully delivering mission-critical solutions. We have extensive industry experience in the financial, insurance, Health IT, media, marketing, retail, and government markets. We have a proven track record in understanding client s business challenges, determine a customer-focused solution, and provide the technical implementation and documentation to bring it to fruition.Job Description: The Data Scientist Analytics role has work across the following four areas: 1) Product Leadership (30%) Evaluating and defining use cases for potential product ideas Lead a team of data scientists to implement complex ML solutions and data products Influencing business partners through presentation of data-based recommendations Communicating of state of business, experiment results, etc. to internal and external partners Spreading best practices to analytics teams 2) Exploratory Analysis (30%) Proposing what to build in the next roadmap Understanding ecosystems, user behaviors, and long-term trends Identifying levers to help move key metrics Evaluating and defining metrics Building models of user behaviors for analysis or to power production systems 3) Data Infrastructure (20%) Working in Hadoop and HIVE primarily Explore the AWS Cloud platform and AWS SageMaker tool Authoring pipelines via SQL and Spark or Python based ETL framework Building key data sets to empower operational and exploratory analysis Performing and automating analyses using statistical language R & Python 4) Product Operations (20%) Designing and evaluating experiments monitoring key product metrics, understanding root causes of changes in metrics Building and analyzing dashboards and reports Requirements:

• 8+ Years data science research or industry experience
• Python proficiency It's our lingua franca, and we're big Jupyter fans
• MS or PhD in CS or STEM Ability to transform concepts into practical solutions
• Team Lead Experience Experience leading a data science team to implement ML solutions
• Machine Learning experience Successful implementation of ML solutions
• Communication Ability Experience/comfort in presenting abstract concepts
• Project Management Experience Experience leading large DS/ML projects
• Cloud Technology Experience Experience working with cloud infrastructure and track record in successful migration to cloud from on-prem
• Healthcare Experience Experience with data science/ML techniques as applied to Healthcare, specifically experience on recommendation engines for members and claims anomaly detection

• Advanced proficiency in Python and Spark/Scala for classical statistical analysis and data modeling, machine learning and ETL processes.
• Ability to write production-ready code including documentation and unit tests.
• Team Lead experience (i.e., managing tasks for other Data Scientists; Lead communicator to client and other DEA Team Leads; good communication skills orally and in writing)
• Experience with machine learning methods like k-nearest neighbors, random forests, ensemble methods and more.
• Proficiency in data science modeling AI, Machine Learning, Deep Learning, Decision Trees, Random Forest, Neural Networks, Supervised/Unsupervised Learning, Forecasting, Predictive Modeling and Clustering.
• Strong background in machine learning using unsupervised and supervised methods.
• Deep knowledge of fundamentals of machine learning, data mining and statistical predictive modeling, and extensive experience applying these methods to real world problems
• Fluency in SQL and other programming languages. Some development experience in at least one scripting language (PHP, Python, Perl, etc.)
• Proven experience of using Python Machine Learning & Data Pre-processing Libraries. (Scikit Learn, Numpy, Pandas)
• Experience working with cloud technologies and infrastructure
• Ability to initiate and drive projects to completion with minimal guidance
• The ability to communicate the results of analyses in a clear and effective manner

• Preferred experience with a statistical package such as R, MATLAB, SPSS, SAS, Stata, etc.
• Proficiency with healthcare analytics and data structures is preferred.
• Desired interdisciplinary skills include big data technologies, ETL, statistics and causal inference, Deep Learning, modeling and simulation.
• Experience working in the AWS cloud platform and AWS SageMaker tool
• Intermediate to advanced ability to create data visualizations using Python.
• Leading data science projects or teams (as the most technically advanced team member) or working independently on data science projects.
• Experience with large data sets and distributed computing (Hive/Hadoop) a plus.
• Strong skills in software prototyping and engineering with expertise in applicable programming and analytics languages (Python, R, Spark/Scala) and various open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work.
• Capacity to convert to a full time positions without a need for current or future sponsorship