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Senior Data Science – ML Engineer – IETCSSDS001- Immediate Closing 130 views13 applications

Innovative is seeking a bright and enthusiastic Senior Data Science – ML Engineer who can hit the ground running. Our client is rapidly expanding our Enterprise Solutions Delivery team.  As such, there is enormous opportunity for learning, innovating and being involved in the Data analysis. We need a hard-working, self-starter with a can-do attitude to join our growing team of systems professionals. You will be part of a core team delivering cutting-edge services to very large business customers and mass-market consumers on a global stage.

The ideal candidate will have experience in troubleshooting new system environments and leading proposed fixes. They will have an aversion to manual tasks and an instinct for automating repetitive tasks into programs and scripts. They will have a solid knowledge of PKS/ AWS. Most importantly, they will be cautiously curious and seek out opportunities for innovation, learning, and responsibility.

Enterprise Solutions Delivery develops cutting edge innovative closed-loop analytics solutions, enabling insights-driven decision making across the enterprise. We collaborate with multiple functional areas and impact every element of our business: corporate, security, networks, retail, IT and others.  We are looking for a result-oriented Data Scientist / ML Engineer who will discover and solve problems by analyzing large amounts of data, defining new metrics and business cases, designing simulations / experiments, creating ML software and models, collaborating with colleagues to develop closed-loop analytics / automation software solutions and reporting. You will be responsible for data modeling, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. You will need to understand the business objectives, systems, and data pipeline. You will translate real world problems into data science problems.

You will solve these problems using appropriate assumptions, methodologies, current data science best practices and developing necessary software. You will work with different teams to identify areas for efficiency improvements.
Essential Functions:
• Support ML projects from strategy through implementation and on-going improvements.
• Perform data collection, analysis, validation, cleansing, developing software in support of multiple machine learning workflows, integrating / deployment of code in a large-scale production environments and reporting.
• Designs, codes, tests, debugs, and documents ML code – models, ETL processes, SQL queries, and stored procedures.
• Extracts and analyzes data from various structured and unstructured sources, including databases, files, data lakes and external APIs/websites.
• Responds to data inquiries from various groups within client’s organization.
• Requires experience with relational databases, document databases (NOSQL) and knowledge of query tools and/or statistical software.
• Responsible for other duties/projects as assigned by business management / leadership.

Minimum Required
• 9  plus years of experience in statistical modeling, data mining, analytics techniques, machine learning software development and reporting
• 5 plus years of applied experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural       Networks, Random Forest, etc., and key parameters that affect their performance.
• 5 plus years of hands-on experience with Python and/or R programming and statistical packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.
• 3 plus years of experience in building use cases / solutions especially around AI/ML cognitive services, based on Cloud infrastructure and services such as Azure cloud platforms and Onpremise
• Expertise with SQL, noSQL, Python, R, Javascript programming languages and big data environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes etc.)
• Experience developing experimental and analytic plans for data modeling processes, using strong baselines, and determining cause and effect relations.
• Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects.
• Expertise with scaling pilot machine learning solutions to a large scale production environment
• Expertise with visualization tools such as PowerBI, D3JS etc.
• Excellent written and verbal communication skills.

• Bachelor or Masters degree in highly quantitative field (computer science, or electrical engineering, mathematics, statistics) or equivalent domain specific experience in lieu of a degree.
• Proficient in machine learning data workflows, data collection methodologies, and data analysis.
• Experience with architecting, designing, developing software solution in Azure and on-prem environments.
• Certifications AI / ML and Azure Cloud platforms

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