Data Scientist

Description:Job DescriptionCandidate Profile: ML Data ScientistAn ideal machine learning engineer candidate will have extensive experience in data analytics and machine learning with proven experience in integrating data pipelines to enable machine learning. This candidate must be able to surface solutions that solve both nebulous business problems and meet technical challenges in bringing together data to enable advanced machine learning. This senior candidate should be comfortable defending elegant solutions in front of stakeholders and mentoring junior developers.Technical Skills1. Python (Numpy, pandas, scikit etc.)2. Tensorflow, Keras, Pytorch, Scikit-learn, XGBoost3. Strong Experience regression regression models (Linear, Logistic)4. Experience with NLP, Computer Vision, Time series data etc. is a plus5. Strong Experience with unsupervised and supervised learning methods6. SQL7. Spark8. AWS platforms such as S3, Glue, Athena, Sagemaker, LamdaAdditional Skills1. Communicating solutions in writing2. Presenting solutions to diverse stakeholders (data engineers, economists, business leaders)3. Creating structure for ambiguous problems4. Providing scalable solutions for business challengesSkills:Python, Machine learning, Data science, Predictive modelling, Predictive analytics, AwsTop Skills Details:Python, Machine learning, Data science, Predictive modelling, Predictive analyticsAdditional Skills & Qualifications:Additional Skills & QualificationsBasic qualifications:• Ability to work backwards from customer needs, and distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives• Strong analytical and quantitative skills with the ability to use data and metrics to back up assumptions, recommendations and drive actions• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-expert audience• Master’s degree (or Bachelor's degree + 5 years of experience) in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science• 3+ years of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication• 3+ years of experience using data querying languages (e.g. SQL), scripting languages e.g. Python, or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)• 0-2 years of research experience working in statistical analysis• Experience using AWS technologies such as Redshift, S3, EC2, EMR and data pipelinesPreferred qualifications:• Master's degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least 4 years of working experience as a Data or Research Scientist• 5+ years of industry experience working as a DS or related specialty• Background designing successful analytics solutions from start to finish• Knowledge of or background with public cloud services• Compelling communication and influencing skills and participation with demonstrated experience engaging and influencing senior executives• Experience in implementing machine learning models in production to support real-time inference is a plus• Must have experience in Python, SQL, Stata, R and/or Scala.• Experience with modelling large individual-level datasets• Experience of finding pExperience Level:Expert LevelAbout TEKsystems:We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.