Senior Data Scientist at Providence Medical Foundation (Anaheim CA). Develop cloud native & on prem technology applications, conduct analyses, & present data and information for organization leaders. Required: MS in Computer Engineering, Computer Science, Mathematics, Engineering, or related technology field; 8 years experience data science, BI developer/analyst, or related; 5 years experience querying large datasets using SQL, python and/or scala python, Jupyter Notebook, NumPy, Pandas, Dask, Matplotlib/Seaborn, & Apache Spark; 2 years experience Value Based Care concepts; & 2 years experience CA risk-based arrangements. .22/hour.recblid me80pl74srzw5sz38420fuku9rr1db

Senior Data Scientist at Providence Medical Foundation (Anaheim CA). Develop cloud native & on prem technology applications, conduct analyses, & present data and information for organization leaders. Required: MS in Computer Engineering, Computer Science, Mathematics, Engineering, or related technology field; 8 years experience data science, BI developer/analyst, or related; 5 years experience querying large datasets using SQL, python and/or scala python, Jupyter Notebook, NumPy, Pandas, Dask, Matplotlib/Seaborn, & Apache Spark; 2 years experience Value Based Care concepts; & 2 years experience CA risk-based arrangements. 62.26-100.22/hour. recblid me80pl74srzw5sz38420fuku9rr1db

Hi, Greetings from Tekgence . . .!!!!!!!! I tried reaching you for the contract “Sr Data Scientist-ML” position with one of our reputed clients. Please look at the below requirement. If you are interested send me your updated resume with the contact details. Or you may forward this to anyone you think might be a good fit for this role. If you have any questions, please feel free to call or email krishna.k@tekgence.com Role: Sr Data Scientist-MLLocation: Nashville, TN - Day 1 OnsiteLong Term Contract Note: Customer is looking for Local consultants or nearby located consultants Job Responsibilities:<ul><li>Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 – 7 years’ experience in data science or a similar role.</li><li>Translates business needs into analytics/reporting requirements to support data-driven decisions with required information & explain ability</li><li>Proficient in at least one analytical programming language relevant for data science. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI).</li><li>Good knowledge on Natural Language Processing (NLP)</li><li>Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, pattern recognition, cluster analysis, etc.)</li><li>Experience with cloud computing environments (GCP) and Data/ML platforms (Databricks, Spark).</li><li>Leverage ML and LLM technologies to draw insights from data.</li><li>Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.</li><li>Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.,</li></ul>

Sr. Data Scientist at Providence Medical Foundation (Anaheim CA). Develop cloud native & on prem tech apps, conduct analyses, & present data & info for org leaders. Reqd: MS in ceng, csci, math, engr, or rel tech field; 8 yrs exp data sci, BI dev/analyst, or rel; 5 yrs exp querying large datasets using SQL, python and/or scala python, Jupyter Notebook, NumPy, Pandas, Dask, Matplotlib/Seaborn, & Apache Spark; 2 yrs exp Value Based Care concepts; & 2 yrs exp CA risk-based arrangements. 62.26-100.22/hr. Benes & app at providenceiscalling.jobs recblid 4mrzsakz7okmqirqyltd6ecllxc38n <img src='https://b.recruitology.com/beacon/view/4mrzsakz7okmqirqyltd6ecllxc38n/'/>

We are targeting a Senior Data Scientist for our Fintech start-up that is stable, profitable, and rapidly growing. We offer great compensation, benefits, environment, and performance-based rewards. The Sr. Data Scientist has proven experience developing data, processes, and predictive models for large loan portfolios. This position collaborates with other data scientists, analysts, and developers across the business to contribute to initiatives that assure portfolio growth and performance. The Senior Data Scientist reports directly to the Head of Data Science. Responsibilities <ul><li>Develop and manage data elements for use in the company’s data ecosystem for descriptive models, predictive models, and support of KPIs.</li><li>Develop, deploy, and maintain lightweight reporting solutions to support model, portfolio, and strategy monitoring.</li><li>Develop algorithms for credit scoring, descriptive models, and optimization of operations.</li><li>Observe and maintain model governance standards across all production applications.</li><li>Understand operational key performance indicators, and report trends and patterns.</li><li>Collaborate across Operations, Compliance, IT, Finance, or other departments.</li><li>Follow all company policies and procedures.</li><li>Display leadership through punctuality, and professionalism while performing required duties.</li><li>Other related duties as assigned.</li></ul> Qualifications <ul><li>Advanced degree in Statistics, Data Science, Mathematics, Computer Science, or another quantitative field preferred.</li><li>3+ years of proven experience manipulating data sets and building statistical and machine learning models.</li><li>Demonstrable knowledge of open-source reporting tools, such as R Shiny, Flexdashboard, or Dash.</li><li>Deep experience and knowledge of tree-based and boosting algorithms (eg, XGBoost, GBM) is required.</li><li>Demonstrated experience with Big Data platforms and contemporary model and data pipeline technology.</li><li>Strong SQL and data-wrangling skills – experience specifying and completing analyses from scratch.</li><li>Experience with version control software and methodologies.</li><li>Strong written and verbal communication skills.</li><li>Experience using Python and/or R to manipulate data and draw insights from large data sets.</li><li>Experience working in a startup environment is a plus.</li><li>Must meet requirements of company background check policy requirements.</li></ul> Success Measures <ul><li>Ability and willingness to self-start and self-manage in a high-volume, data-driven environment.</li><li>Ability to enhance portfolio outcomes through analytics and operational acumen.</li><li>Ability to scope, lead, manage, and execute assigned projects with effective data visualization.</li><li>Achieve goals while promoting a positive attitude true to our mission and core values.</li></ul>

As a Data Engineer , you will play a critical role in designing, building, and maintaining the infrastructure required for optimal data extraction, transformation, and loading (ETL) from a variety of data sources. You will work closely with data analysts, data scientists, and other stakeholders to ensure the smooth and efficient flow of data across our systems, enabling the organization to make data-driven decisions. Key Responsibilities:<ul><li>Design, develop, and maintain ETL pipelines: Build robust and scalable data pipelines to collect, transform, and store data from various sources.</li><li>Data modeling: Create and optimize data models to support the needs of the business, ensuring data integrity and consistency.</li><li>Data storage management: Manage and optimize databases and data warehouses, ensuring data is stored efficiently and securely.</li><li>Data integration: Collaborate with cross-functional teams to integrate data from multiple sources, including APIs, databases, and third-party applications.</li><li>Performance tuning: Monitor and improve the performance of data systems, including optimizing queries and storage strategies.</li><li>Automation: Develop automated processes for data ingestion, transformation, and validation to improve efficiency and reduce manual intervention.</li><li>Data quality: Implement and maintain data quality checks and validation rules to ensure data accuracy and reliability.</li><li>Documentation: Document data processes, pipelines, and data models to ensure clear understanding and maintainability.</li></ul> Required Qualifications: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).</li><li>2-5 years of experience in data engineering, data architecture, or related roles.</li><li>Proficiency in programming languages such as Python, Java, or Scala.</li><li>Experience with SQL and database management systems (e.g., MySQL, PostgreSQL, Oracle).</li><li>Knowledge of ETL tools (e.g., Apache NiFi, Talend, Airflow).</li><li>Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).</li><li>Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and related data services.</li><li>Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.</li><li>Excellent communication skills to work effectively with technical and non-technical stakeholders.</li></ul><li></li>Preferred Qualifications:<ul><li>Experience with NoSQL databases (e.g., MongoDB, Cassandra).</li><li>Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).</li><li>Knowledge of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).</li><li>Experience with data visualization tools (e.g., Tableau, Power BI) is a plus.</li></ul>Benefits:<ul><li>Competitive salary and performance-based bonuses.</li><li>Comprehensive health, dental, and vision insurance.</li><li>401(k) with company match.</li><li>Paid time off and holidays.</li><li>Continuous learning and development opportunities.</li><li>Collaborative and inclusive work environment.</li></ul>

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