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Mid-Level Data Scientist (Python/Spark) [$231k/yr+] TS/SCI-FSP

SYSTOLIC, INC.
Annapolis Junction, MD, United States
about 2 months ago
Apply on www.clearancejobs.com
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
10 years minimum
Compensation
$231,000.0
Working hours
Regular working hours
Job source
www.clearancejobs.com

Tech stack

Big Data Cloud Computing Extract Transform Load (ETL) Data Flow Control Python (Programming Language) Data Processing Apache Spark Data Pipelines

Job description

  • Develop and implement solutions using Python and Apache Spark for large-scale data processing.
  • Conduct in-depth network and protocol analysis.
  • Oversee and optimize dataflow and ETL (Extract, Transform, Load) processes., * Utilize Python and Apache Spark for development and data manipulation.
  • Work comfortably with large-scale data environments.
  • Apply strong network and protocol analysis background to complex problems.
  • Manage and optimize ETL, dataflow, and data processing pipelines.
  • Leverage Cloud repository/Big Data technologies.

Requirements

  • Degree: Technical bachelor’s degree or equivalent experience
  • Years of experience: 10+ years
  • Total Compensation: $231k+ yearly

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.clearancejobs.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

2:34 min

Capabilities of the Apache Spark processing engine

Ayon Roy · LIVE

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

6:08 min

Applying software engineering environments and testing to data pipelines

Matthias Niehoff Matthias Niehoff · World Congress 2024

47 sec

Building modern data pipelines for legacy exports

Dr. Alexander Wachtel Dr. Alexander Wachtel +1 · World Congress 2025

2:04 min

Comparing offline data analytics with online stream processing

Artem Volk Artem Volk +1 · World Congress 2024

Videos

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PySpark - Combining Machine Learning & Big Data thumbnail
43:26
LIVE • almost 6 years ago

PySpark - Combining Machine Learning & Big Data

Ayon Roy

Why and when should we consider Stream Processing frameworks in our solutions thumbnail
30:51
World Congress 2024 • about 2 years ago

Why and when should we consider Stream Processing frameworks in our solutions

Soroosh Khodami

Alibaba Big Data and Machine Learning Technology thumbnail
43:57
LIVE • almost 6 years ago

Alibaba Big Data and Machine Learning Technology

Qiyang Duan

Implementing continuous delivery in a data processing pipeline thumbnail
34:00
LIVE • almost 6 years ago

Implementing continuous delivery in a data processing pipeline

Álvaro Martín Lozano

Python-Based Data Streaming Pipelines Within Minutes thumbnail
39:04
LIVE • almost 2 years ago

Python-Based Data Streaming Pipelines Within Minutes

Bobur Umurzokov

Let's Get Aggregated: Custom UDAFs in Spark thumbnail
19:58
World Congress 2025 • about 1 year ago

Let's Get Aggregated: Custom UDAFs in Spark

Nikolai Nikolaev

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