46 Data Science Engineer Jobs

Responsibilities

1. Build world-class ML models.
2. Design, run and analyze A/B and multivariate hypothesis tests aimed at optimizing customer experience, business KPIs and product funnels.
3. End to end development and testing of the solutions as per the requirements.
4. Be involved in technology research, capability building across newer technologies and tools in the ML ecosystem at scale.
5. Influence business decisions to help improve consumer and network experiences.
6. Spot new business opportunities and drive growth.
7. Partner and work closely with engineering and product teams to build world class data products.
8. Mentor data scientists.

Minimum Qualifications

1. Deep understanding of Statistical Analysis, Modeling and Machine Learning algorithms.
2. 3+ years of experience with machine learning model development. Experience in designing and deploying ML modeling and prediction pipelines.
3. Good command over Python, Tensorflow/PyTorch/Jax, PySpark.
4. Strong coding skills with the ability to write high-performance code in Python/Julia/R. Familiar with version control.
5. Must be fluent with SQL.
6. Ability to contribute to multiple projects/demands simultaneously and work in a fast-paced, collaborative and iterative environment.

Preferred Qualifications

1. M.S./Ph.D. in Computer Science / Statistics / Applied Mathematics.
2. Strong Python skills for data wrangling/analysis/visualization and modeling.
3. Experience with distributed big data computing (Hadoop / Spark). Experience with Presto/Druid for ad-hoc analysis.
4. Experience with mlflow and/or airflow for data pipelines and model deployment.
5. Experience with Neural Networks (e.g. RankNet, MLP or LSTM) and NLP (e.g. Word2Vec). Deployed at least one industrial project using supervised/unsupervised machineRole & responsibilities

Preferred candidate profile

Perks and benefits