Data Scientist IV

Posted 22 Days Ago
Be an Early Applicant
Philippines
60K-120K
Senior level
Hardware • Machine Learning • Software
The Role
The Data Scientist IV role involves developing machine learning models, analyzing data, mentoring team members, and communicating insights to stakeholders to drive business decisions.
Summary Generated by Built In

We are DemandScience, a global company which never stops innovating in our mission to provide the healthiest and most predictive global B2B data and intelligence for our customers. Our clients include sales and marketing professionals at global companies. Excellent execution is in our DNA. We provide innovative AI-analytics merged with enriched data to identify your next in-market prospects and customers at scale.


Position Summary:

Playing a crucial role in guiding statistical and machine learning techniques to analyze data, build predictive models, and develop data-driven solutions in addition to extracting knowledge and insights from complex and diverse datasets to inform business decisions and drive innovation.


Essential Job Functions “What You’ll Do”:

  • Works on problem of diverse scope where analysis of data and ML models requires in-depth evaluation all factors including perspective from industries and technologies available to solve the problem.
  • Seasoned, experienced professional with full understanding of at least one area of specialization and can resolve wide range of issues in creative ways.
  • Demonstrates good judgement in selecting methods and techniques for obtaining solution.
  • Normally receives very little instructions on day-to-day work and general instruction on new assignments.
  • Follows standard practices and procedures in analyzing data and presenting the results.
  • Work with large, structured, and unstructured datasets to identify patterns, trends, and anomalies.
  • Clean, preprocess, and validate data to ensure accuracy and reliability for analysis.
  • Use statistical methods and data visualization tools to interpret and present findings to stakeholders.
  • Develops and implements machine learning algorithms and predictive models to solve business problems.
  • Applies data mining techniques to discover insights and patterns in data.
  • Continuously refine and optimize models to improve performance and accuracy.
  • Work on projects involving natural language processing (NLP), computer vision, recommendation systems, etc., as needed.
  • Determines methods and procedures on new assignments and lead team members.
  • Excellent written and verbal communication skills. Able to convey complex ideas to a broad audience of different specializations.
  • Strong sense of ownership and focus on long-term usability and extensibility.
  • Emphasis on exploring, experimenting, and innovating on current patterns and designs.
  • Mentors other Data Scientists

 

Essential Qualifications “What You’ll Need”: 

  • Bachelor's Degree in Computer Science, Mathematics, Statistics, or related discipline
  • 8+ years machine learning model development with expertise in at least one domain (language or visual or speech) and has implemented multiple ML-based projects including all tasks that are needed for introducing the solution in a product/ solution.
  • Proficiency in languages like Python, R, and optionally Java, C.
  • Proficiency in using software development IDEs like Jupyter notebook, and source code maintenance tools like GitHub or equivalents.
  • Proficiency in using one or more SQL databases (MySQL, Postgres...), or NoSQL databases (Redis, MongoDB, DynamoDB...).
  • Understanding and experience in applying ML libraries like pandas, scikit-learn for data analysis, and ML frameworks like SpaCy, Rasa etc.
  • Worked in cloud environment (AWS, Azure or GCP) for data transportation.
  • Ability to build simple data pipeline for implementing machine learning algorithms.
  • Proficiency in applying one of more: classification algorithms (K-nearest, SVM, Decision trees etc.), time-series algorithms (ARIMA etc.), forecasting techniques, and an understanding of neural-network-based algorithm architectures (like RNN, LSTM etc.).
  • Analytical and problem-solving skills, with the ability to work with large and complex datasets.
  • Communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders.
  • Has built data pipelines on cloud environment (AWS, Azure or GCP) that requires complex transformation and transportation of data.
  • Has built machine learning and natural language processing models by training, hyperparameter tuning, validating, and testing models from scratch, in at least one medium complexity commercial projects.
  • Understand all basic tasks associated with NLP domain.
  • Has good working knowledge of applying deep learning frameworks such as TensorFlow, Pytorch or Keras and transformers libraries from open source (e.g., HuggingFace) for natural language processing tasks.
  • Has good understanding of neural-network-based algorithm architectures (like RNN, LSTM etc.) and transformer architectures (like Bert and other variations).
  • Has built, implemented, and maintained data pipelines on cloud environment (AWS, Azure or GCP) that requires complex transformation and transportation of data.
  • Has built machine learning and natural language processing models by training, hyperparameter tuning, validating, and testing models from scratch, in more than two medium complexity commercial projects or at least one high complexity commercial project.
  • Deep understanding all basic tasks associated with NLP domain with implementation experience in at least one of the following tasks: text classification, entity recognition, sentiment analysis, machine translation, conversational bots, or document retrieval using latest NLP techniques.
  • Has implemented solution using deep learning frameworks such as TensorFlow, Pytorch or Keras and transformers libraries from open source (e.g., HuggingFace) for natural language processing tasks.
  • Has implemented customization in standard neural-network-based algorithm and transformer architectures.
  • Has implemented model validation and testing methods and understands model selection criteria based on business, real-world-data, and performance considerations.
  • Understands MLOps framework and has experience in using open-source tools (like MLFlow, DVC etc.) and/or cloud-based solution (like AWS SageMaker, Azure Machine Learning, or Google Cloud AI Platform etc.).

 

THE GOOD STUFF!

We embrace diversity and inclusion and encourage our amazing team members at DemandScience to bring their authentic, fun selves to work every day. We offer a culture of innovation, mutual respect, support, and transparency.  The competitive and comprehensive benefits our team members enjoy are designed to ensure you and your family members are healthy. Check this out!

  • Paid time off
  • Medical provided through HMO
  • Life Insurance
  • Peer-Appreciation Program
  • Employee Referral Program
  • A fast-paced, innovative culture with an open and collaborative environment, where you can make an impact.
  • Join a great organization that cares about employees!

DemandScience is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

#LI-Remote

Find out more at https://demandscience.com/careers/#join-the-team

Top Skills

AWS
Azure
C
Dvc
DynamoDB
GCP
Git
Java
Jupyter Notebook
Keras
Mlflow
MongoDB
MySQL
Pandas
Postgres
Python
PyTorch
R
Rasa
Redis
Scikit-Learn
Spacy
TensorFlow
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The Company
Greater Boston
1,141 Employees
On-site Workplace
Year Founded: 2012

What We Do

DemandScience is the premier B2B demand generation company accelerating global growth for our clients. The DemandScience intelligence platform empowers B2B organizations to swiftly identify the right accounts and target in-market buyers with precision. By combining groundbreaking technologies, machine learning and data science innovation, the company ensures timely delivery of accurate data, intelligence, and insights, adding value to the end-to-end journey from initial engagement to conversion. Founded in 2012, DemandScience provides 1,500 global customers with superior marketing solutions, B2B data, and leads. With a team of 600+ employees across operations in seven countries, DemandScience is certified as a Great Place To Work, named #5 on Fortune Magazine’s 2022 list of the Best Workplaces in Advertising & Marketing, and one of only 143 companies in history to be named to the Inc. 5000 for 10 consecutive years. For further insights on why DemandScience stands at the forefront of transformative demand generation

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