Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. Experience working with cross functional teams (Data Science teams a plus.

The Business Data Analyst, Senior will report to the Sr. Manager of Back Office Analytics. Requires proficiency in SAS, R, or Python (preferred) for data wrangling, automation, and creating statistical and machine learning models.

In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.

Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. Data science will have an introduction with PYTHON, further into numerical python, PANDAS DATA ANALYSIS, DATA VISUALISATION.

Strong knowledge of Python (Pandas DataFrames and accessing APIs), Azure (DevOps and Function Apps), PostgreSQL, QGIS and/or ESRI ArcGIS to perform data analysis and visualization. Utilize tools such as Python (Pandas DataFrames and accessing APIs), Azure (DevOps and Function Apps), PostgreSQL, QGIS and/or ESRI ArcGIS to perform data analysis and visualization.

Extracts data using a variety of a programming languages, such as SQL, SAS, Python, or Spark/Scala, and applies knowledge of relational and non-relational database systems housed on both on-premise and off-premise (hybrid) platforms.

KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.

Position Summary: The Senior Manager of Data Analytics predominately uses a tech stack of Power BI, SQL, Visual Studio Code, Snowflake, and Excel to answer questions to data that is ETL’d from our ERP, CRM, and various internal and external data sources.

Minimum 5 years of experience utilizing various tools such as Python, R, SQL, or Tableau, and reporting platforms with the ability to represent data through reports, dashboards, scorecards, or KPIs. In lieu of 5 years of analytics tools experience, a Master's Degree in a relevant program plus 2 years of experience will be considered.

Some of the high priority skills include: quantitative research; experience modeling for predictive analytics and program evaluation; experience with R and/or Python, and natural language processing; process/clickstream data analysis; and machine learning (e.g. unsupervised learning, predictive analysis, automated feature extraction.

Location:Tysons, VA (Hybrid) with some remote work·Work Authorization:EAD, Green Card or ·Work Type:Full Time Responsibilities include, but are not limited to: Gathering and cleaning HR data from various sources, such as HRIS, ATS, surveys, and external benchmarksPerforming descriptive, inferential, and predictive analysis using statistical methods and tools, such as Excel, SQL, R, Python, Power BI, Tableau, etc.

As a Data Analytics or Data Engineer Intern , you will play a key role in developing a more data driven culture at Pacific Life. Interns will use industry leading tools such as Python, R, Sales Force, and Alteryx to help solve real world business problems.

Net, C#, Android SDK, Kotlin, IOS Swift, AWS: EMR, S3, Redshift, Athena, Glue, DynamoDB, Lamda, CloudWatch, ElastiCache, Kinesis, SNS, SQS, Azure: HDInsight, Data Factory, Data Lake Analytics, Databricks, GCP, and Big Data Apache: Hadoop, Hive, Hue, Sqoop, Kafka, Spark, Airflow, SnowFlake, Python, Scala, Machine Learning: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Apache Mahout, Vertex AI, Keras, OpenNN, Theano.

Proven experience in leading solution engineering or product design and associated methodsExperience w/Mixed data sets and approaches (analytics, analytic tools, data science)Exceptional understanding of cutting-edge analytics, technologies, consumer behavior, and travel industryProficiency with Python, SQL, Snowflake, Databricks, Tableau, PowerBI and other commonly used analytics, data management and business intelligence applications.

The courses may include Foundations of Data Analytics and Programming, Advanced Excel for Data Analytics, Data Governance, Management and Quality, Data Visualization-Power BI, Data Visualization-Tableau, Data Privacy and Integrity, Data Protection, Descriptive Analytics, Predictive Analytics, Data Complexity, Cloud Analytics, Big Data, various programming courses and concepts involving python, r and ML, and database courses (including MySQL, Microsoft SQL Server and NoSQL alternatives.