Senior Data Scientist

Engineering & Development Los Angeles, California


Martindale-Avvo is looking for an experienced Data Scientist to help lead our machine learning effort. The ideal candidate has a practical background in machine learning, with experience in natural language understanding, information retrieval, knowledge extraction, or deep learning. The role is located in sunny El Segundo, and you’ll be working closely with our business units in Seattle, New Jersey, and Austin.  You will be helping to lead the machine learning effort, working with product engineers and data scientists in building content recommendation, personalization, and business intelligence models to enhance our customer experience and business intelligence capabilities.

- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods.
- Extending company’s data with third party sources of information when needed.
- Processing, cleansing, and verifying the integrity of data used for analysis.
- Doing ad-hoc analysis and presenting results in a clear manner.
- Apply machine learning, collaborative filtering, NLP, and deep learning methods to massive data sets.
- Collaborate with cross-functional agile teams of software engineers, domain experts, and others to build new product features for multiple business units.
- Collaborate with data scientists across a variety of businesses to prioritize and promote our machine learning efforts.

Skills and Qualifications:
- B.S., M.S. or PhD in Computer Science, Software Engineering, Information Science, Mathematics, Statistics, Electrical Engineering, Physics or related fields or equivalent experience.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience with common data science toolkits, such as R, Scikit-learn, NumPy, Tensorflow.
- Strong knowledge in POS tagger, shallow and deep parser, feature scaling, dimensionality reduction & data compression techniques, TF-IDF, SVM, Ensemble models (Bagging, Boosting), model tuning using grid-search etc.
- 5+ years of software development experience in NLP development & or text analytics.
- 5+ years of experience implementing machine learning systems at scale in Python (preferred), Scala, or Java.
- You care about agile software processes, data-driven development, reliability, and responsible experimentation.
- You preferably have machine learning publications or work on open source to share with us.

Excellence in at least one of these is highly desirable:
- Experience with data visualisation tools, such as D3.js, GGplot, etc.
- Proficiency in using query languages such as SQL.
- Experience with NoSQL databases.
- Experience with data processing and storage frameworks like Hadoop, Spark, Kafka, etc.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by federal, state, or local law.

Success starts with having the right people. At Internet Brands, we value and mentor each member of our growing team. We seek out talented, goal-oriented professionals who live and breathe the Internet and thrive in a flexible but challenging work environment. Our team of innovators has enabled Internet Brands to sustain high levels of profitability and success while evolving along with the Internet for over 20 years.

At IB, we promote an entrepreneurial, friendly culture that applauds innovation and results while embracing change and independence. Our employees are intensely driven and constantly encouraged to reach higher and use creativity to achieve success – all the while enjoying high levels of collaboration and the luxury of coming to work in jeans and sneakers. We are proud to offer a unique blend of the innovation of a start-up with the history, stability, and benefits of an established corporation.