Data Scientist

Job Description

Job Title
Data Scientist

I. Job Summary | Major goals and objectives.

With over 25 million surveys collected annually from thousands of retailers worldwide, Bizrate Insights is one of the largest sources of verified customer-generated seller ratings and reviews, helping both retailers and consumers make informed decisions. We believe great technology empowers organizations. At Synapse Group, we're using technology to optimize our business, recognize when things are going right (and occasionally wrong) and provide data and insights that let our business make decisions in the modern, fast-paced environment.

Los Angeles, CA or New York, NY candidates are preferred, but we are open to remote accommodations for the right person.
• If you are a passionate Data Scientist who is excited to see the impact of your hard work in production, optimizing and driving business strategies, come join a team of like-minded, skilled professionals where you can learn and share your knowledge!
• You will be participating in activities across the data science lifecycle: business case definition, data collection, cleaning, integration, analysis, visualization, feature engineering, modeling with machine learning algorithms, deployment, A/B testing, interpreting the models/results, and reporting.
• Communicating and coordinating effectively with product managers, software engineers, analytical groups and customer-facing teams in an agile environment.
• Working with data processing pipelines for analyzing gigabyte- to terabyte-scale data from multiple sources. Designing actionable data products based on statistical analysis and machine learning methods and working on their deployment to enterprise systems, optimizing the business at Synapse / Bizrate Insights and Dotdash Meredith.
• Learning continuously in the areas of data science, machine learning, ad technology, forecasting, marketing operations, natural language processing, data ecosystems, content operations, social media analysis and industry standard measurements.

II. Essential Job Functions

Weight % - Accountabilities, Actions and Expected Measurable Results

35% - Leverage your technical expertise to constantly raise the bar and ensure the team delivers extraordinary results – focusing on creating value, continuous improvement, and collaboration. Strive to thoroughly understand customer, business and stakeholder needs, and provide effective data driven solutions to meet those needs. Develop, communicate, and maintain architectural, design, and lineage documentation.

20% - Enhancing, upgrading and maintaining previously developed Data Science products

15% - Brainstorming and developing new data driven solutions to evaluate, consult and optimize various business proposals

15% - Participating in Retros, demos, planning, daily stand up

15% - Learning and continuous improvement (keep up with state-of-the-art technology, conferences

100%

III. Minimum Qualifications and Job Requirements | All must be met to be considered.

Education:

B.S. or Masters (Preferred) in Engineering, Computer Science, Statistics or Mathematics or other quantitative fields

Experience:

2+ Years of Data Science experience and data scripting languages (e.g. Python, SQL, R etc.), understanding all practical details of the entire pipeline of Data Science: data query from data warehouse and datalakes, dataset creation, exploration of data, data cleansing, statistical analysis, feature engineering, model training and evaluation, model deployment and monitoring.

Specific Knowledge, Skills and Abilities:
• Solid understanding of popular machine learning algorithms including supervised, un-supervised, and semi-supervised ones. What is the difference between algorithms? What algorithm would you choose for a given problem and why? What are the pros and cons of these algorithms? What is cross-validation, hold-out sample, RMSE, overfitting, biasz/
• Proficient in one or more core data science programming languages (Python) and the ability to develop code in emergent languages and APIs as needed especially Java and Scala
• Practical experience in building a full cycle machine learning engine from cleansing data to training and hyperparameter optimization to methods for evaluating the accuracy to identifying the ways to improve the accuracy of the model.
• Experience in data applications working with large-scale distributed systems (e.g. EMR, Spark, Hadoop)
• Exposed to and experienced with state-of-the-art machine learning toolkits such as Spark ML, TensorFlow, Scikit-learn, XGBoost, NLP … preferably in Big Data frameworks (e.g. Apache Spark).
• Familiarity with AWS ecosystem, Sagemaker, Athena, EMR, QuickSight, etc
• A self-learner with capability to switch from the independent contributor and leader of the project to a collaborative contributor on the team (and vice versa) depending on the demand of the project and the availability of the resources.
• Collaborate with stakeholders, partners, and clients to ensure that all parties are aligned and supportive of the project's priorities, requirements, timeline, and objectives.
• Familiarity with the MapReduce paradigm and Apache Spark project.
• Proficient with SQL as a means of gathering data from relational databases.
• Practiced data manipulation and mining of structured and unstructured data.
• Experience in visualizations for business stakeholders using a variety of visualization tools from libraries in Python and MS Excel,
• Familiarity with Data Engineering tools such as ETL, AWS Glue, Datalake, Airflow
• Superior written and verbal communication with both technical and non-technical audiences
• Strong analytical skills and a results-driven mindset

% Travel Required (Approximate):

Pay Range
Salary: $98000 - $130000

Jobcode: Reference SBJ-rv20on-18-226-166-64-42 in your application.