Senior Analytics Engineer

About TSR:

TSR is a relationship-based, customer-focused IT and technical services staffing company.

For over 40 years TSR, Inc. and its wholly owned subsidiary, TSR Consulting Services, have prospered in the Information Technology staffing business, earning the respect of companies both large and small with well refined candidate screening, timely placement, and a real understanding of the right skill sets required by our clients.

Mission & Vision

We do not believe in building a vision around the company but building a company around our vision, which is simply;

Every employee's voice matters, their effort is appreciated, and their talent is rewarded.

We challenge each employee daily, to raise the bar on how we treat our consultants and candidates. For far too long in this industry, candidates have been ghosted, lied to, or placed at a client and then forgotten about. Each day our staff works tirelessly at qualifying and placing, top talent with our clients, in a compassionate and caring manner.

Not every candidate is a match for the job, but every candidate and consultant will be treated with respect and professionalism.

Senior Analytics Engineer

Job Description

• Location: Summit, New Jersey
• Type: Contract
• Job #80229

Our client, a leading pharmaceutical company, is hiring a Senior Analytics Engineer, on a contract basis.

Job ID #: 80229

Work Location:
Summit, NJ - 50% on site

Knowledge/Skills:

• Advanced SQL skills (5+ years)
• 2 years experience working with dbt
• 5 years working with relational databases
• MS in Computer Science, Chemical Engineering, Biostatistics or similar with 6 years industry experience or PhD in Computer Science, Chemical Engineering, Biostatistics or similar with 3 years industry experience
• Intermediate python skills
• Intermediate visualization (tableau, dashboarding) experience

Education/Experience:

• MS in Computer Science, Chemical Engineering, Biostatistics or similar with 3-6 years industry experience or PhD in Computer Science, Chemical Engineering, Biostatistics or similar with 3 years industry experience
• Dashboard development experience (Tableau, Spotfire, DASH)
• Proficient in writing and developing analytical and machine learning models using python modules including pandas, numpy, scikitlearn, and tensorflow. Experiencing developing and implementing MLOps pipelines.
• Experience building analytical and statistical models to answer key business questions
• Experience using git via the command line
• Strong understanding of core statistical concepts to solve real world problems
• Intermediate to advanced proficiency (3+ years post academia experience as an independent contributor designing and delivering data solutions) in SQL.
• Experience interacting with various data warehouses and large-scale, complex datasets using ETL and BI tools and platforms.
• Self-motivated to identify and propose novel methodologies that will drive increased efficiency
• demonstrate expert knowledge in machine learning and rule-based systems as applied to computational linguistics and natural language processing, as well as development and execution of annotation tasks with teams of experts
• Proficiency in mathematics with the skill to translate complex mathematical algorithms into usable computational methods
• Experience with data mining and analysis techniques across disparate data sources
• Experience working in LINUX/UNIX environments
• Experience interacting with PostgresSQL, Oracle, Impala Cloudera, Okera or similar databases
• Experience with JupyterLabs, Anaconda, and RStudio
• Intermediate proficiency with python
• Experience developing visualizations using a variety of methods (plotly, matplotlib, seaborn)
• Experience working within Domino Data Lab projects
• Technical knowledge of performance tuning and query optimization across large data sets.
• Experience with data cataloguing and enablement through APIs
• Experience with a variety of computer science languages (C++, Java, html/css)
• Exposure to bioprocess engineering/cell therapy data
• Knowledge of GxP requirements (preferably related to data and code management)
• Experience with Program/Project Management. SCRUM experience highly desired

Preferred:

• Familiar with NET/SAP
• Knowledge of deep learning methods for NLP (quantitative area of study, Computer Science, preferred)
• Strong background and demonstratable experience in Natural Language Processing and Computational Linguistics is required
• Experience working with the pharmaceutical industry
• Experience working with ERP systems

Responsibilities:

• Performs data engineering, preprocessing, exploratory data analysis, and model development by interacting with a variety of databases
• Responsible for ingestion, integration and delivery of data across multiple platforms
• Works to maintain and uphold data integrity and clean data principles
• Responsible for leading team code review and improving team programming practices
• Responsible for independently coordinating and managing analytics projects across several departments and with cross functional stakeholders
• Ability to work on a global team and communicate across several time zones
• Communicates with team members regularly to provide updates and collaborate on deliverables.
• Accountable for leading, documenting and managing analytics URS and UAT through execution for GPO
• Lead and engage colleagues who complete data related activities
• Design and deliver digital solutions that streamline access to analytics & data
• Work with domain SMEs to derive insight and value to improve manufacturing related data transformations and improvement initiatives.
• Displays a high level of teamwork and collaboration both within and across functions
• Utilizes supervised or unsupervised methods, learning from vast amounts of unlabeled data to drive insight
• Experience working with unstructured text
• Ensures life cycle management of code is maintained through version control and associated repositories.
• Develops high quality analytical and statistical models, insights, patterns, visualizations, that can be used to improve decision making in manufacturing operations.
• Responsible for documentation of all technical work both within and outside of formal document management systems
• Independently develops code and analytical models to automate data transformation and analysis