DATA SCIENTIST JOB DESCRIPTION

We are in search of a Data Scientist who will be pivotal in transforming raw data into actionable insights by crafting innovative visualizations and engineering key features to enhance modeling strategies, grounded on rigorous evaluation metrics. This role entails collaborative work with different teams to decipher their requirements into machine learning or statistical challenges, contributing to the development of data-centric products. It demands a high level of expertise in exploratory data analysis, the creation of predictive models, and the effective dissemination of analytical findings to stakeholders, aiming to seamlessly integrate data-driven insights into strategic business decisions.

An Overview of Data Scientist Job Description Responsibilities and Qualifications

1. Join our Global Data Science Center of Excellence as a Data Scientist and elevate business outcomes through innovative, efficient solutions. Develop and apply Machine Learning tools and data processing pipelines, tackling client challenges in data-driven engagements. Collaborate closely with experts, under the guidance of Senior Data Scientists and Project Managers, to design and implement ML models that drive superior business results.

Data Scientist Functions:

  • Process, cleanse, and verify the integrity of data used for analysis;
  • Identify, interpret and communicate meaningful insights from data sources to clients and internal interdisciplinary teams;
  • Identify opportunities to improve data collection and management procedures;
  • Test and select the most appropriate ML methods for specific applications, validate and deploy data analytics models to achieve business results;
  • Communicate effectively within the data science team, systems team, and customer-facing teams to ensure models and results are well understood and incorporated into their business processes.
  • Working knowledge of cloud technologies;
  • Working knowledge of data visualization tools;
  • A postgraduate degree in mathematics, statistics, computer science, engineering or another quantitative field;
  • Keenly interested in analyzing and solving challenging industrial problems;


Data Scientist Qualifications:

  • Bachelor’s degree in Engineering, Computer Science, Mathematics or equivalent from an accredited University;
  • 3-5 years of experience developing and applying ML models in industrial (preferred) and business settings,
  • Excellent knowledge and understanding of ML techniques and algorithms;
  • Experience in data cleaning/ processing;
  • Experience in quantitative analysis/research of large, complex data sets;
  • Working knowledge of Python.
  • Experience and knowledge of process simulation software;
  • Demonstrated ability to work both collaboratively and independently when appropriate;
  • Ability to build relationships and effectively influence colleagues, clients and stakeholders;
  • Excellent communication, interpersonal and teamwork skills.

2. As a Data Scientist on the Success Services team, you will be responsible for the technical design, implementation, and delivery of our customers’ data for use cases that are not served directly through the product. You will be responsible for managing existing data services, as well as driving all net-new data deliverables owned by Success Services. In addition to the engineering work, you will consult directly with customers, enabling them to build use cases with People.ai data on top of their own infrastructure.

Data Scientist Responsibilities:

  • Serve as the most technically advanced member of the Success Services team as it pertains to data ingestion and manipulation skills
  • Coordinate internally with appropriate technical teams to provide a seamless experience to our customers
  • Work across Product, Technical Success, and Services to simplify and scale the entire portfolio of Services offerings
  • Lead logical architecture design in collaboration with Product and Technical Success to enable scalable data models that support value delivery to customers
  • Assist customers with API configuration and ingesting People.ai data into their analytics infrastructure
  • Enable customers on People.ai activity data to support their own use cases
  • Build custom dashboards leveraging our Executive Analytics Platform (embedded BI in web app) along with Product
  • Create customer-facing documentation for our top dashboards
  • Optimize refresh schedules for data pipelines and dashboards, both internally and externally
  • Own the delivery and development of the Historical Contacts Service in coordination with Technical Success
  • Conduct a backend data design audit of top 5 use cases to ensure scalability moving forward


Data Scientist Qualifications & Experience:

  • Extensive (5+ years) of coding (e.g. Python, Java, Scala) and data modeling experience
  • Experience with enterprise data analytics architecture, developing data pipelines, and using various ETL libraries/tools
  • Experience building reports in BI tools (e.g. Tableau, Looker, Power BI, Sisense) on top of data warehouses (e.g. Redshift, Snowflake, BigQuery)
  • Expert at extracting and manipulating data from multiple sources, including relational databases and REST APIs
  • Working knowledge of cloud-based big data technologies (e.g. Spark, Hive, Hadoop)
  • Comfortable consulting with customers to enable them to leverage People.ai data within their infrastructure
  • Must be very organized and know how to accurately and thoroughly document all solutions produced
  • Values teamwork and good at building partnership cross-functionally
  • Open to feedback and ideas from others
  • Creative and innovative
  • Analytical, data-driven and high-level problem solver

3. The Data Scientist role focuses on harnessing advanced analytical tools to enhance demand forecasting precision significantly. By employing descriptive statistics, multivariate analysis, and machine learning, the position aims to uncover and alert the business to emerging trends early. This critical function supports a comprehensive project to integrate new OMP supply chain planning software, ensuring analytical models are accurate and actionable. Working in tandem with Demand Managers, the Data Scientist validates model outputs, integrating them into IBP consensus demand forecasts for credible business planning. Reporting to the Continuous Improvement Team Leader, this role is pivotal in developing, deploying, training, and monitoring best practices, directly contributing to the execution of the E&I Supply Chain Strategy and achieving global business objectives.

Roles of Data Scientist:

  • Identifying and selecting relevant, credible data sources, and collecting, integrating, and mining data,
  • Analyzing patterns in data; building models, designing experiments, and testing hypotheses.
  • Becoming proficient with the demand analytics aspects of the OMP tool to perform the following types of tasks in OMP
  • Conducting/updating forecast ability studies
  • Performing multivariate data analysis using historical and predictive leading indicator data
  • Working with SMEs and business team members to interpret data modeling results and incorporate into monthly Demand Management processes
  • Providing internal E&I support for ongoing analysis and model tuning/updates.
  • Driving business results by communicating complex quantitative analysis in a clear, precise, and actionable manner.
  • Working closely with business stakeholders, which are made up of cross-functional teams across organizational boundaries (Demand, Supply, Sales, Marketing, Product Management).
  • Being a trusted advisor to the Demand Managers and other business leaders.
  • Incorporating data model results into managing processes such as the Differentiated Forecast Strategy.
  • Monitoring the performance of the demand process to continually improve accuracy and reduce bias.
  • Mentoring Data Analysts with the goal of improving their analytical skills.
  • Representing E&I as a member of the DuPont corporate Center of Competency Demand Planning advisory group, and networking with others doing similar work inside and outside DuPont. 


Qualifications of Data Scientist:

  • Ph.D. or MS/BS in statistics, math, or engineering, with 5 or more years of data analytics experience and a strong computing background.
  • Expertise using deep learning, machine learning, and neural networks for time series analysis.
  • Enhancing knowledge through demand analytics industry groups and continuing technical education.
  • Experience using statistical scripting languages, preferably R and Python.
  • Basic knowledge of relational databases and SQL is a plus.
  • Strong business acumen with the ability to translate business problems to data analytics requirements, and design applicable data models and analytics pipelines to resolve the problems.
  • Excellent communication and customer-facing skills, with the ability to explain technical approaches and rationale of findings in easy to understand terms for the business.
  • Strong leadership and collaboration skills.
  • Global teamwork experience (leadership role or significant interface as part of teams, leading teams, working cross-cultures) preferred.

4. The Data Scientist will be responsible for surfacing insights from our data that drive decision-making, improve our offerings, and solidify our data platform. Your analysis will contribute to our product roadmap, engagement, acquisition, offerings, and more. You will be working within a startup environment that requires flexibility and nimbleness, where good communication and willingness to make a real contribution is key to success. As with any growing company, many other tasks and responsibilities should be expected to be assigned, and growth opportunities to be seized.

Duties of Data Scientist:

  • Inform our product roadmap from strategy to execution through research and analysis of pre-existing large data sets.
  • Drive data projects from start to finish that improve our product offerings and customer experience. 
  • Continuously evaluate current and new data sources; explore possibilities to increase/decrease relevant data capture.
  • Work collaboratively on projects with cross-functional teams.
  • Lead efforts to define and build the next generation of our data platform.
  • Identify and incorporate new internal data sources with our development team.
  • Collaborate with business, product, and marketing leadership on new business opportunities identified from data-driven insights.
  • Work closely with cross-functional teams from investor relations to real estate operations to farm analysts, as well as product owners, engineers, designers, marketers, and others across our organization all of whom are incredibly passionate about our marketplace.
  • Leverage new and existing data to enhance decision-making within the organization.
  • Measure and report the health of initiatives and track them through metric-driven dashboards.
  • Provide ad-hoc data analysis and reporting as needs arise.
  • Present informed opinions on work and solutions to potential problems to internal stakeholders. 
  • Begin providing targets and current performance updates on a bi-monthly basis to management.
  • Understand AcreTrader’s mission and core values
  • Clearly articulate the vision for AcreTrader as well as the core beliefs of the company.
  • Be able to defend thoughts and ideas internally in a professional manner when challenged.


Requirements of Data Scientist:

  • Experience developing information out of complex, varied sourced, and many times, unstructured datasets
  • Proficiency in Python, SQL, and structured and unstructured data; experience with ML libraries and frameworks would be a bonus
  • Ability to use business sense to balance decision making
  • Experience working in Github and using Git commands
  • Experience working with RESTful APIs
  • Mindset of continuous improvement
  • Ability to self-motivate and self-manage in an unstructured environment, comfortable with ambiguity
  • Strong written, verbal, and interpersonal communication skills
  • Minimum five years experience as a data analyst, data scientist, and/or data engineer
  • Located or willing to relocate to Fayetteville, AR

5. The Data Scientist role involves leveraging machine learning techniques to draw insights from data, enhancing business processes, and identifying potential new business opportunities. Skills in Python and SQL are essential, along with experience in developing NLP, classification, and deep learning models.

Responsibilities of Data Scientist:

  • Utilise machine learning techniques to develop models and insights to solve business problems
  • Experiment and quickly build out proof of concepts to test feasibility and demonstrate potential solutions to the business
  • Identify opportunities for improvement through data, and champion the usage of data to derive insights and drive action across the business
  • Work with cross functional team to analyse opportunities and gaps, research and understand technologies and applicability of these technologies to Element
  • Prior experience as a Data Scientist or relatable role
  • Develop best practices and coach others on data collection and usage.
  • Be curious! Recognize insights and trends from our data that will improve our platform and overall customer experience.
  • Explore new technologies and analysis practices to identify efficiency and growth opportunities.
  • Within 30 days, develop a deep understanding of AcreTrader’s business and customer offerings.


Qualifications & Experience of Data Scientist:

  • Bachelor's degree in information technology, computer science, engineering, data science or a related field will be appropriate
  • Strong statistical and machine learning understanding
  • Experience in Manufacturing, Testing, and Industrial domain
  • Analytical/critical thinking with proven ability to look for opportunity areas to improve business performance
  • Excellent communication skills with proven ability to communicate potentially complex ideas in a simple form to all types of audiences
  • Adaptability and flexible to stay current on new technologies
  • Ability to work under pressure in a fast pace environment
  • Project management using Agile techniques
  • A self-starter with experience owning deliverables, and performing detailed self-review of work

6. In the role of the first Data Scientist at this company, harnessing cutting-edge analytics breathes new life into a traditional industry, focusing on pressing issues around hearing loss, product engagement, and determinants of user satisfaction. This position entails the creation and refinement of the data architecture, the development of critical analytics and dashboards, and the democratization of information access for the entire Whisper team. Elevating internal decision-making processes, this role supports the advancement of proprietary ML-based audio processing technologies through close collaboration with the machine learning and audio engineering teams.

Functions for Data Scientist:

  • Collaborating with various business units to identify data-driven, machine learning business opportunities
  • Working with the architecture and product teams as needed to understand company needs, devise solutions, and assist in the integration of trained models into other products or processes    
  • Implementing appropriate statistical, mathematical, or coding methodologies as needed for advanced analytics use cases
  • Selecting features, building and optimizing classifiers, and using machine learning techniques
  • Performing data mining and advanced analytics using appropriate state-of-the-art methods
  • Identifying and extending the company’s data with third-party sources of information when needed
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Collaborating with architecture, product, and business intelligence teams to identify big data opportunities, as well as standardizing advanced analytics to increase the value of those opportunities
  • Keeping up to date with technology trends, specifically analytics, machine learning, AI, and DevOps
  • Processing, cleansing, and verifying the integrity of data used for advanced analysis
  • Performing ad hoc analysis and presenting results clearly


Knowledge, Skills and Abilities for Data Scientist:

  • Educating and mentoring other team members on advanced analytical concepts and processes
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, and Decision Forests
  • Able to conceptualize advanced analytical processes, such as machine learning and deep learning
  • Experience with common data science toolkits and libraries, such as R, Python, Weka, NumPy, and MatLab
  • Good written and verbal communication skills
  • Familiar with data visualization tools, such as D3.js and ggplot
  • Excellent SQL skills
  • Experience with ETL processes and capabilities
  • High level of applied statistics skills, such as distributions, statistical testing, and regression
  • Solid scripting and programming skills in SQL, Python, C#, or Java
  • Data-oriented personality
  • Self-driven, curious, and creative
  • Previous experience with financial services or financial service product delivery a plus
  • PhD in statistics, machine learning, computer science, or the natural sciences, especially physics or any engineering disciplines, desired

7. The Data Scientist plays a crucial role in enhancing business outcomes through the development and application of predictive models. This position involves data preparation, feature engineering, and crafting advanced machine learning and AI algorithms to bolster risk assessment and decision-making processes. Ideal candidates should possess a robust technical expertise, a keen understanding of business strategies, and a dynamic, collaborative approach to drive success.

Data Scientist Details:

  • Uses SQL and other database tools to prepare data for predictive model development.
  • Develops statistical, machine learning and AI models using R or Python
  • Performs model validation, testing and optimization.
  • Works with IT and business intelligence teams on model implementation and validation.
  • Maintains documentation on data sources, scoring and decisioning processes.
  • Assists with designing decisioning policies and procedures that maximize profitability.
  • Interprets and understands business needs, and develops data-driven solutions.


Data Scientist Knowledge, Skills and Abilities:

  • Bachelor’s Degree in computer science or a quantitative discipline
  • Able to write production-quality code and be familiar with software engineering best practices, including testing and version control
  • Ability to communicate their findings to both technical and non-technical audience
  • Strong creative problem solving and communication skills.
  • Strong understanding of statistics, econometrics and machine learning concepts.
  • Experience with data analysis and management using SQL.
  • Experience with machine learning and artificial intelligence algorithms.
  • Experience with predictive model development in Python, R or SAS.

8. The Data Scientist role within the Artificial Intelligence and Digital Solutions team blends start-up agility with the robust support of a large corporation. Tasked with refining manufacturing, QA laboratory, and supply chain processes, this position plays a key role in crafting systems and applications for enhanced process insight and optimization. Additionally, it involves delivering data science consulting, training, and application development.

Data Scientist Duties and Responsibilities:

  • Engage with business teams to find and qualify opportunities, understand requirements, and translate those requirements into technical solutions
  • Conduct and manage data science projects with customer’s pain points and vision of success in mind
  • Design data science approach to provide process improvement support, enhance manufacturing efficiency, product quality, and equipment reliability
  • Enable customers to solve complex business problems through problem framing, data preparation, model building, production deployment, model management, and output consumption
  • Collaborate with data engineers and platform architects to implement robust real-time, production solutions
  • Ensure operational metric health by monitoring production decision points
  • Communicate results of analyses and associated business benefits to business partners and executives
  • Develop templates, design, develop, and integrate systems for repeatable processes
  • Stay current on new technologies and methods across data science, data engineering, and data visualization, share best practices to improve technical capabilities of the team


Data Scientist Knowledge, Skills and Abilities:

  • Master or Ph.D. degree in statistics, data science, computer science, operations research, or closely related field.
  • Candidates with a Bachelor's degree with exceptionally strong data science skills and relevant experience will be considered.
  • Strong Python programming skills
  • Ability to efficiently analyze large complex data
  • Strong problem-solving skills
  • Strong interpersonal skills and team player attitude
  • Creativity and curiosity with the ability to learn and apply new concepts quickly
  • Ability to interact effectively with a wide variety of operations personnel, laboratory personnel, chemists, and IT personnel
  • Experience with designing, building, and deploying machine learning and AI solutions at scale for production to solve business problems is a plus
  • Applied experience working in the manufacturing industry is a plus
  • Experience with Industrial internet of things (IIoT) is a plus
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