Financial Data Specialist

Zvigaro Zvemari DhaunyanzviNha. Postions: 1placeholder Financial Data SpecialistNzvimbo: Mumbai / Pune / Delhi NCR

Financial Data Specialist

Semari yemari Data Specialist mhando ichadikanwa kutsigira DSS (Decision Support System) inotarisa kune FP & A, FRC nedzimwe nzvimbo dzebhizimisi.

mabasa:

Chinotevera Chizvarwa & Benchmarking

  1. Kuvaka mari inotevera chizvarwa chemari chikamu chemari yekushandisa kushandisa Bots, AI, ML, Blockchain, Microservices uye Bigdata pane imwe nzira yemajitiramu akawanda.
  2. Benchmark finance portfolio solutions pakati pezera revezera uye vave pakati pezvakanakisisa

Automation

  1. Itai kuti hurumende yepasitori yezvigadziriswe yeFP & A, R2R, S2P2P, Q2C, A2R, Tax & Treasury pa ECC & S4 HANA pamwe chete nemhinduro yakakodzera yeR & RE.
  2. Kuvaka sarudzo yekugadzirisa inoita kuti zvirongwa zvakajeka zvekuita / kutaurirana nechepfupi kudzokorora pfungwa
  3. Gadzirai nzira nekugadzirisa pakati peMarikiti yemari uye nzvimbo yakakura yebhizimisi yezvigadzirwa zvekugadzirisa kusarudzwa kwebhizimisi rekugadzirisa dambudziko remhinduro.
  4. Sotsigira mari uye mari inokonzerwa nekuderedza kupera uye mazano ekubvisa kushandiswa pazvikamu zvakasiyana-siyana zvekubata maoko.

Kuteerera Chiratidzo cheChishanu

  1. Vakai nyika yakawanda yakabatanidza mari yekugadzirisa, hurongwa uye sarudzo yekutsigira agility yebhizimisi nebasa.
  2. Kununura zvakanakisisa mukirasi bhizimisi kubudirira pamusoro pekugadzirisa nekugadzirisa kwemabasa ose emari padhipatimendi re digital
  3. Bhenekmark uye kurwira "Kubhadhara", "Revenue assurance", "kuunganidza uye kubhadhara kubhadhara" kuti ive yepasi rose.
  4. Kuita nekutevedza kwakasimba nekugadzirisa maitiro nekunakisisa "Zvigadziriswa" zvishandiso kwete pane zvishandiso zvekushandisa. 

Zvinoda Jobho:

  • Mvumo yekushanda nematafura makuru kwazvo.
  • Uine ruzivo rwehuwandu hwemashoko, maitiro emagadzirirwo, kuvaka dzimba dzakagadzikana uye dzakachengetedzwa
  • Ziva zvinetso zvingangodaro, edza pfungwa, tsvaga tsvakurudzo dzekutsvakurudza ruzivo uye sarudza nzira yekugadzirisa zvinetso zvekuongorora • Kunzwisisa, kubvisa, kuchenesa uye kugadzirira data yekuongorora
  • Ita tsanangudzo yekuongorora tsanangudzo ye data pane data uye igovera zvitsva
  • Ukana wekunzwisisa makodhi mu data domain tools
  • Mhanyai miedzo kuti munzwisise kushandiswa kwesimba rinotarisirwa remadziro akavakwa uye kushanduka kwekushandura kumabasa uye IT
  • Nyora zvose zvakawanikwa uye kunyatsobatsira kushandiswa kuburikidza nekushandura kuenda kumabasa uye IT
  • Ita mazano ekuvandudzirwa kwemitemo yakatsigirwa nekuongorora zvakawanikwa
  • Gadzira hurukuro yevateereri vakatarwa
  • Isa matanho ekutumira mazano / mazano uye kutumira kana kuti tisati tasvika matanho ekudikanwa kweMikoro
  • Chiitiko neHadoop kugovera se Cloudera, MapR kana Hortonworks
  • Chiitiko muR, Apache Spark (SparkR), Python scripting, PySpark
  • Chiitiko muStatistical Modeling / maitiro ekudzidza semichina seKutarisa kweLinar, RegressionTrees, DecisionTrees kana K - zvinoreva,
  • Unyanzvi hwakanaka hwekugadzirira, zvichida muR uye / kana Python.
  • Inzi-yakadzika yedzivo yekuvakwa kwedhayamisi yekufananidzira uye database yekugadzirisa zvakanakisisa tsika.
  • Maoko pane ruzivo mune makuru makuru ekufambisa uye data yarehousing.
  • Strong hwokukurukura
  • Ruzivo ruchauya nemakore anopfuura 10 ane ruzivo mune zvidzidzo zvemari dzemari.

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